Reconstruction of gene regulatory network of colon cancer using information theoretic approach

Size: px
Start display at page:

Download "Reconstruction of gene regulatory network of colon cancer using information theoretic approach"

Transcription

1 Reconstructon of gene regulatory network of colon cancer usng nformaton theoretc approach Khald Raza #1, Rafat Parveen * # Department of Computer Scence Jama Mlla Islama (Central Unverst, New Delh-11005, Inda. 1 kraza@jm.ac.n * Department of Informaton Systems Kng Abdulazz Unversty, KSA rafatparveen@yahoo.co.n Abstract Reconstructon of gene regulatory networks or 'reverse-engneerng' s a process of dentfyng gene nteracton networks from expermental mcroarray gene expresson profle through computaton technques. In ths paper, we tred to reconstruct cancer-specfc gene regulatory network usng nformaton theoretc approach - mutual nformaton. The consdered mcroarray data conssts of large number of genes wth 0 samples - 1 samples from colon cancer patent and 8 from normal cell. The data has been preprocessed and normalzed. A t-test statstcs has been appled to flter dfferentally expressed genes. The nteracton between fltered genes has been computed usng mutual nformaton and ten dfferent networks has been constructed wth varyng number of nteractons rangng from 30 to 500. We performed the topologcal analyss of the reconstructed network, revealng a large number of nteractons n colon cancer. Fnally, valdaton of the nferred results has been done wth avalable bologcal databases and lterature. Keywords Gene regulatory networks, mcroarray, colon cancer, systems bology I. INTRODUCTION Cancer, medcally known as a 'malgnant', s a knd of dsease nvolvng unregulated cell growth. The cancerous cells are dvded and grown uncontrollably formng malgnant tumors and nfest the nearby part of the body. The possble means to dagnose cancer are chemotherapy, radotherapy and surgery but unfortunately, these methods of treatment often damage healthy cells and tssues. Therefore, dentfcaton of molecular markers of cancers may be an alternatve approach to dagnose the human cancer and mght be useful for development of novel therapes. Although, varous sgnfcant genes responsble for the geness of dfferent tumors have been revealed but fundamental molecular nteractons are stll unclear and remans a challenge for the researchers. Due to rapd growth n mcroarray technology, gene expresson of tens of thousands of genes can be measured smultaneously n a sngle experment usng a small amount of test sample that enable the researchers detect cancerous molecular markers [1]. Mcroarrays have been successfully used n many bomedcal applcatons such as gene dscovery, dsease dagnoss, drug dscovery and toxcology. A typcal mcroarray gene expresson data s a matrx R wth N rows and M columns, where rows represent genes and column as samples (or envronmental condtons or tme-pont). Due to expermental lmtatons, major problem wth mcroarray data are dmensonalty problem (M<<N) and presence of nose n expresson values. Mcroarray-based cancer predcton s new and growng area of research. A gene regulatory network (GRN) tres to model the complex regulatory nteractons wthn the lvng cells and gve a realstc representaton of gene regulaton. The nference of GRN from mcroarray s referred as 'reverseengneerng. Mcroarray gene expresson profles of whole genome can be used to understand cancer and to reconstruct cancer-specfc GRN. The changes n expresson profle of genes across varous samples provde nformaton that can be used to flter dfferentally expressed genes between normal and tumor samples and helps to fnd regulatory relatonshps between gene-pars whch lead to the reconstructon of GRN. Mappng the topology of GRNs s a central ssue n systems bology research []. Also, accurate computatonal methods to reconstruct genome-scale GRN from gene expresson profles are requred to explore these expermental data n new and more ntegratve way. Many computatonal methods have been proposed n the lterature to model GRNs ncludng drected graph, Boolean networks, generalzed Bayesan networks, lnear and nonlnear ordnary dfferental equatons (ODEs), machne learnng approach, and so on. An extensve revew can be found n [, 3, 5, 6, 15]. Many others have tred to reconstruct cancer-specfc GRNs usng gene expresson profles [4][7]. In [4], a cancer-specfc (prostate cancer) GRN has been reconstructed usng Pearson's correlaton coeffcent (PCC) and a network of few most sgnfcant genes and ther nteractons has been dentfed. A comprehensve comparatve evaluaton of many state-of-the-art GRN nference methods has been done by Madhamshettwar et. al. [7]. Fnally best-performng method has been appled to nfer GRN of ovaran cancer. Many other attempts has been made to reconstruct GRN of varous cancers ncludng colon cancer, ovaran cancer, lungs cancer and breast cancer. In ths work, nformaton theoretc approach called mutual nformaton has been used to compute regulatory relatonshps between gene-pars. We appled ths approach to reconstruct

2 GRN of colorectal cancer (CRC), the thrd leadng cause of cancer mortalty world-wde, whch s a genetc dsease, propagate by the acquston of somantc alternatons that nfluence the expresson level of gene. II. MATERIALS AND METHODS In systems bology, many gene regulatory network (GRN) nference methods use nformaton theoretc approach as an estmator to unvel the nteracton and relatons among genes n a cellular system from gene expresson profles. One of the ntal method based on mutual nformaton for GRN nference was ntroduced n [8]. Ths method, called relevance network (RN), assgns edges to gene pars f the correspondng MI value s above a gven threshold. The networks that result from applcaton of RN are assocaton networks because an edge between two genes ndcates ther assocaton but not necessarly a causal effect. Another types of nference methods are also avalable that ntend to fnd out causal nteractons among genes and ther products whch can be valdated wth bologcal experments, avalable databases and lteratures. Tll now, there s no generally agreed gold standard to conduct and nclude the routne of gene regulatory network nference and ther analyss for molecular studes. However, essental preprocessng steps of the data are requred to prepare them for the subsequent nference of a gene regulatory network nvolve standardzed procedures for the normalzaton of gene expresson dstrbutons wthn and between samples and a summarzaton step to obtan genecentrc values of the gene expresson [9]. In ths paper, we have appled mutual nformaton to fnd the regulatory relatonshp between gene-pars. A. Algorthm for the reconstructon of gene regulatory network The man steps for the reconstructon of gene regulatory networks are outlned as follows: (1) Data preprocessng and normalzaton. () Identfcaton of sgnfcant genes. () Computaton of MI among gene pars. (3) Elmnaton of week correlaton lnks. (4) Computaton of adjacency matrx and network generaton. (5) Bologcal valdaton of the results. (6) Druggablty analyss An sketch of the proposed method s shown n Fg. 1. B. Identfcaton of sgnfcant genes Before gene expresson data s analyzed, frst t s ensured data the data set ncludes genes that dffer n ther expresson level sgnfcantly between two classes of samples. Many methods are avalable for dentfcaton of dfferentally expressed genes n the lterature ncludng fold-change, t-test statstcs, ANOVA [10] rank product [11], Sgnfcant Analyss of Mcroarray (SAM) [14], Random Varance Model (RVM) [1], Lmma [1], and so on. Due to wde applcatons and sgnfcant results of t-test statstcs for samples havng two dfferent classes (e.g. cell types, cancer types, expermental condtons), we appled t-test to dentfy dfferentally expressed between the two classes normal and tumour. The t-test for unpared data and both for equal and unequal varance can be computed as [4], where x and y are the means, g and h are the varances, and n 1 and n are the szes of the two groups of the sample (condtons) tumor and normal, respectvely, of gene expresson profle. Fg. 1 Steps of the proposed methodology C. Estmaton of Mutual Informaton The mutual nformaton (MI), based on nformaton theory, s a general measure for the nonlnear dependence of the two random varables. It s generalsaton of parwse correlaton coeffcent used to compare expresson profles of a set of mcroarrays and to measure the degree of ndependence between two genes. For each par of genes, ther MI(x, s computed and the edge a xy =a yx s set to 0 or 1 dependng on a sgnfcant threshold. Mutual nformaton, MI(x,, between gene x and gene y s computed as: MI ( x, H ( x) H ( H ( x, () where entropy H can be defned as: n H ( x) p(( x )log( p( )) (3) k 1 t 1 k x k y x g h n n (1)

3 and the jont entropy H(x, s defned as, H ( x, p( x, y ) log( p( x, y )) (4) xx y jy j j From the defnton, the MI becomes zero f the two random varables x and y are statstcally ndependent [that s, p(x,=p(x)p(], as ther jont entropy H(x,= H(x)+H(. A hgher MI value specfes that the two genes are non-randomly connected to each other. The MI descrbes an undrected graph because t s symmetrc, MI(x,=MI(y,x). MI s more generalzed than the Pearson correlaton coeffcent (PCC) because t quantfes only lnear dependences between varables. However, MI and PCC yeld almost dentcal results. Accordng to the defnton of MI, t requres each samples (experment) to be statstcally ndependent from the others and thus ths approach can deal wth steady-state as well as wth tme-seres gene expresson data. III. RESULTS AND DISCUSSIONS In the present study we took the mcroarray data of crculatng plasma RNA dataset of colorectal cancer (CRC) patent consstng of 0 samples collected from CRC patents. Out of 0 samples, 1 are from colon tumors and 8 are from normal bopses. The dataset contans the expresson profles of 1555 genes obtaned by measurng the relatve abundance of the dfferent RNA speces n plasma through cdna mcroarray hybrdzaton, by comparng RNA solaton and amplfed from colorectal cancer patents and from healthy donors. We downloaded the full data set from Gene Expresson Omnbus (GEO) [13]. Fg. shows the comparatve vew of gene expresson of dfferent samples for both colon cancer samples and normal samples. The expresson of sample profles n normal tssue s hgher n comparson to that of cancer tssue n most of the cases. Many of the cancer sample profles are down-regulated, as shown n Fg.. Fg. Sample profle graph showng expresson values n cancer and normal sample. Gene expresson data contans a large number of genes, the majorty of whch may not be relevant for analyss. We appled t-test statstcs to select most sgnfcant genes from the above dataset whose p-values are less than We also elmnated those genes whose ether gene name s not avalable or most of the values n expresson profles are mssng. In ths way, we found 101 most sgnfcant genes that have been selected for further analyss. To fnd the regulatory nteractons among the selected sgnfcant genes, mutual nformaton between gene pars has been computed usng equaton (). Now gene nteracton network has been constructed, where nodes correspond to gene names and parwse mutual nformaton s allocated to the edge between genes. Intally, we took the top 30 hghest par-wse MI values (can be assumed as nteracton weght) for the network constructon and found a network of genes, whch s shown n Fg. 3. From the Fg. 3, t s clear that gene ACAT s hghly connected wth a degree of 9 and regulatng a large number of genes. Smlarly, we constructed nne other network by takng top 40, 50, 60, 70, 80, 90, 100, 50 and 500 MI values and observed the fve hghly connected genes n each case. The observaton of fve hghly connected genes n each of the network s shown n Table 1. From the Table 1, t s clear that as the number of nteractons are ncreases, the degree of each hub genes are ncreases. The network 10 consders 500 nteractons that nvolves 79 genes, n whch fve hghly connected genes are ACAT(54), CYP1B1(50), NPM1(48), COX15(46), CREM(4), where numbers n parenthess shows the connecton degrees. The network 10 s shown n Fg. 4. Fg. 3 Network of genes and 30 nteractons

4 Fg. 4 Network of 79 genes and 500 nteractons Table 1. Ten dfferent networks, number of genes nvolved n each, fve hghly connected genes wth ther degrees. Network No. No. of nterac tons Number of genes Top fve genes wth hghest degree Network 1 30 ACAT (9), FABP5 (6), NPM1(6), COX15(5), CYP1B1(5) Network 40 5 ACAT(9), FABP5(9), NPM1(8), CYP1B1(8), CREM(6) Network ACAT(1), NPM1(11), CYP1B1(10), FABP5(10), SNCA (7) Network ACAT(14), NPM1(13), CYP1B1(11), FABP5(10), SNCA(7) Network ACAT(14), NPM1(13), COX15(1), CYP1B1(1), FABP5(10) Network CYP1B1(16), ACAT(14), NPM1(13), COX15(1), SNCA(11) Network ACAT(17), CYP1B1(16), NPM1(14), SNCA(13), TNKS(13) Network NPM1(18), ACAT(17), CYP1B1(16), SNCA(13), TNKS(13) Network CYP1B1(34), NPM1(33), COX15(30), ACAT(30), CREM(8) Network ACAT(54), CYP1B1(50), NPM1(48), COX15(46), CREM(4) The dentfcaton of hghly connected genes (hubs) may play a vtal role n cancer dagnoss and therapes. The extracted genes has been valdated wth the avalable bologcal databases and lteratures and found that most of the dentfed genes ncludng ACP, LDHA, SPARCL, EPAS1, MVP, OXA1L, RPL10A, etc. are nvolved n colon cancer. All the dentfed nteracton among genes ncludng hghly connected genes needs bologcal valdaton for ts relablty. Further, the proposed method can be appled to benchmark as well smulated dataset for ts accuracy measure. IV. CONCLUSIONS Our study shows applcaton of nformaton theoretc approach to colon cancer, demonstratng how ths approach can reveal novel gene regulatory nteractons n case of cancer. We constructed ten dfferent networks by varyng the number of nteractons rangng from 30 to 500, as shown n Table 1. The dentfed sgnature n frst network captures the regulatory relatonshps among dfferentally expressed genes. In case of tenth network consderng 500 nteractons, t shows regulatory relatonshps among 79 dfferentally expressed genes. Our study resulted three major outcomes. Frst, we dentfed dfferentally expressed genes n colon cancer patent, most of them are bologcal verfed and found to partcpate n colon cancer. Second, the nteractons between dfferentally expressed genes has been dentfed, whch needs further bologcal valdaton. Thrd, we dentfed genes regulatng most of the other genes (hubs). The utlty of our approach and the relablty of the obtaned results needs further expermental valdaton. These fndngs may help to reveal the common nteracton mechansm of colon cancer and provde new nsghts nto cancer dagnostc and therapy.

5 REFERENCES [1] X. Wang and O. Gotoh, Mcroarray-based cancer predcton usng soft computng approach., Cancer nformatcs, vol. 7, pp , Jan [] S. R. Maetschke, P. B. Madhamshettwar, M. J. Davs, and M. A. Ragan, Supervsed, sem-supervsed and unsupervsed nference of gene regulatory networks, arxv: v1, 013. [3] H. De Jong, Modelng and smulaton of genetc regulatory systems: a lterature revew, Journal of computatonal bology, vol. 9, no. 1, pp , 00. [4] K. Raza and R. Jaswal, "Reconstructon and Analyss of Cancerspecfc Gene Regulatory Networks from Gene Expresson Profles," Internatonal Journal on Bonformatcs & Boscences, vol. 3, ssue, pp. 5-34, 013. arxv: v1, 013. [5] G. Karlebach and R. Shamr, Modellng and analyss of gene regulatory networks., Nature revews. Molecular cell bology, vol. 9, no. 10, pp , Oct [6] K. Raza and R. Parveen, Evolutonary Algorthm n Genetc Regulatory Netowrks Model, Journal of Advanced Bonformatcs Applcatons and Research, vol. 3, no. 1, pp , 01. [7] P.B. Madhamshettwar, et al, "Gene regulatory network nference: evaluaton and applcaton to ovaran cancer allows the prortzaton of drug targets," Genome Medcne, vol. 4:41, 01. [8] A. Butte and I. Kohane, "Mutual nformaton relevance networks: functonal genomc clusterng usng parwse entropy measurements," Pac Symp Bocomput 000, pp , 000. [9] R. de Matos Smoes and F. Emmert-Streb, "Influence of Statstcal Estmators of Mutual Informaton and Data Heterogenety on the Inference of Gene Regulatory Networks," PLoS ONE, vol. 6, ssue 1, pp. e979, 011. [10] M. Kerr, M. Martn and G. Churchll, "Analyss of varance for gene expresson mcroarray data," Journal of Computatonal Bology, vol. 7, pp , 000. [11] R. Bretlng, P. Armengaud, A. Amtmann and P. Herzyk, "Rank products: a smple, yet powerful, new method to detect dfferentally regulated genes n replcated mcroarray experments," FEBS Lett., vol. 573, ssue 1-3, pp. 83-9, 011. [1] G. Wrght, R. Smon, "A random varance model for detecton of dfferental gene expresson n small mcroarray experments," Bonformatcs, vol. 19, pp , 003. [13] M. Collado, et. al., "Genomc proflng of crculatng plasma RNA for the analyss of cancer," Cln Chem, Vol. 53, ssue 10, [14] V. Tusher, R. Tbshran and G. Chu, "Sgnfcance analyss of mcroarrays appled to the onzng radaton response," Proc. of the Natonal Academy of Scences of the Unted States of Amerca, vol. 98, pp , 001. [15] K. Raza and R. Parveen, Soft Computng Approach for Modelng Genetc Regulatory Networks, Advances n Computng and Informaton Technology, vol. 178, pp. 1 1, 01.

Gene Selection Based on Mutual Information for the Classification of Multi-class Cancer

Gene Selection Based on Mutual Information for the Classification of Multi-class Cancer Gene Selecton Based on Mutual Informaton for the Classfcaton of Mult-class Cancer Sheng-Bo Guo,, Mchael R. Lyu 3, and Tat-Mng Lok 4 Department of Automaton, Unversty of Scence and Technology of Chna, Hefe,

More information

International Journal of Emerging Technologies in Computational and Applied Sciences (IJETCAS)

International Journal of Emerging Technologies in Computational and Applied Sciences (IJETCAS) Internatonal Assocaton of Scentfc Innovaton and Research (IASIR (An Assocaton Unfyng the Scences, Engneerng, and Appled Research Internatonal Journal of Emergng Technologes n Computatonal and Appled Scences

More information

Parameter Estimates of a Random Regression Test Day Model for First Three Lactation Somatic Cell Scores

Parameter Estimates of a Random Regression Test Day Model for First Three Lactation Somatic Cell Scores Parameter Estmates of a Random Regresson Test Day Model for Frst Three actaton Somatc Cell Scores Z. u, F. Renhardt and R. Reents Unted Datasystems for Anmal Producton (VIT), Hedeweg 1, D-27280 Verden,

More information

Joint Modelling Approaches in diabetes research. Francisco Gude Clinical Epidemiology Unit, Hospital Clínico Universitario de Santiago

Joint Modelling Approaches in diabetes research. Francisco Gude Clinical Epidemiology Unit, Hospital Clínico Universitario de Santiago Jont Modellng Approaches n dabetes research Clncal Epdemology Unt, Hosptal Clínco Unverstaro de Santago Outlne 1 Dabetes 2 Our research 3 Some applcatons Dabetes melltus Is a serous lfe-long health condton

More information

Copy Number Variation Methods and Data

Copy Number Variation Methods and Data Copy Number Varaton Methods and Data Copy number varaton (CNV) Reference Sequence ACCTGCAATGAT TAAGCCCGGG TTGCAACGTTAGGCA Populaton ACCTGCAATGAT TAAGCCCGGG TTGCAACGTTAGGCA ACCTGCAATGAT TTGCAACGTTAGGCA

More information

Project title: Mathematical Models of Fish Populations in Marine Reserves

Project title: Mathematical Models of Fish Populations in Marine Reserves Applcaton for Fundng (Malaspna Research Fund) Date: November 0, 2005 Project ttle: Mathematcal Models of Fsh Populatons n Marne Reserves Dr. Lev V. Idels Unversty College Professor Mathematcs Department

More information

This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and

This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and Ths artcle appeared n a journal publshed by Elsever. The attached copy s furnshed to the author for nternal non-commercal research and educaton use, ncludng for nstructon at the authors nsttuton and sharng

More information

INTEGRATIVE NETWORK ANALYSIS TO IDENTIFY ABERRANT PATHWAY NETWORKS IN OVARIAN CANCER

INTEGRATIVE NETWORK ANALYSIS TO IDENTIFY ABERRANT PATHWAY NETWORKS IN OVARIAN CANCER INTEGRATIVE NETWORK ANALYSIS TO IDENTIFY ABERRANT PATHWAY NETWORKS IN OVARIAN CANCER LI CHEN 1,2, JIANHUA XUAN 1,*, JINGHUA GU 1, YUE WANG 1, ZHEN ZHANG 2, TIAN LI WANG 2, IE MING SHIH 2 1The Bradley Department

More information

Prediction of Total Pressure Drop in Stenotic Coronary Arteries with Their Geometric Parameters

Prediction of Total Pressure Drop in Stenotic Coronary Arteries with Their Geometric Parameters Tenth Internatonal Conference on Computatonal Flud Dynamcs (ICCFD10), Barcelona, Span, July 9-13, 2018 ICCFD10-227 Predcton of Total Pressure Drop n Stenotc Coronary Arteres wth Ther Geometrc Parameters

More information

Nonstandard Machine Learning Algorithms for Microarray Data Mining. Byoung-Tak Zhang

Nonstandard Machine Learning Algorithms for Microarray Data Mining. Byoung-Tak Zhang Nonstandard Machne Learnng Algorthms for Mcroarray Data Mnng Byoung-Tak Zhang Center for Bonformaton Technology (CBIT) & Bontellgence Laboratory School of Computer Scence and Engneerng Seoul Natonal Unversty

More information

Survival Rate of Patients of Ovarian Cancer: Rough Set Approach

Survival Rate of Patients of Ovarian Cancer: Rough Set Approach Internatonal OEN ACCESS Journal Of Modern Engneerng esearch (IJME) Survval ate of atents of Ovaran Cancer: ough Set Approach Kamn Agrawal 1, ragat Jan 1 Department of Appled Mathematcs, IET, Indore, Inda

More information

The Limits of Individual Identification from Sample Allele Frequencies: Theory and Statistical Analysis

The Limits of Individual Identification from Sample Allele Frequencies: Theory and Statistical Analysis The Lmts of Indvdual Identfcaton from Sample Allele Frequences: Theory and Statstcal Analyss Peter M. Vsscher 1 *, Wllam G. Hll 2 1 Queensland Insttute of Medcal Research, Brsbane, Australa, 2 Insttute

More information

IMPROVING THE EFFICIENCY OF BIOMARKER IDENTIFICATION USING BIOLOGICAL KNOWLEDGE

IMPROVING THE EFFICIENCY OF BIOMARKER IDENTIFICATION USING BIOLOGICAL KNOWLEDGE IMPROVING THE EFFICIENCY OF BIOMARKER IDENTIFICATION USING BIOLOGICAL KNOWLEDGE JOHN H. PHAN The Wallace H. Coulter Department of Bomedcal Engneerng, Georga Insttute of Technology, 313 Ferst Drve Atlanta,

More information

Study and Comparison of Various Techniques of Image Edge Detection

Study and Comparison of Various Techniques of Image Edge Detection Gureet Sngh et al Int. Journal of Engneerng Research Applcatons RESEARCH ARTICLE OPEN ACCESS Study Comparson of Varous Technques of Image Edge Detecton Gureet Sngh*, Er. Harnder sngh** *(Department of

More information

310 Int'l Conf. Par. and Dist. Proc. Tech. and Appl. PDPTA'16

310 Int'l Conf. Par. and Dist. Proc. Tech. and Appl. PDPTA'16 310 Int'l Conf. Par. and Dst. Proc. Tech. and Appl. PDPTA'16 Akra Sasatan and Hrosh Ish Graduate School of Informaton and Telecommuncaton Engneerng, Toka Unversty, Mnato, Tokyo, Japan Abstract The end-to-end

More information

Using the Perpendicular Distance to the Nearest Fracture as a Proxy for Conventional Fracture Spacing Measures

Using the Perpendicular Distance to the Nearest Fracture as a Proxy for Conventional Fracture Spacing Measures Usng the Perpendcular Dstance to the Nearest Fracture as a Proxy for Conventonal Fracture Spacng Measures Erc B. Nven and Clayton V. Deutsch Dscrete fracture network smulaton ams to reproduce dstrbutons

More information

AN ENHANCED GAGS BASED MTSVSL LEARNING TECHNIQUE FOR CANCER MOLECULAR PATTERN PREDICTION OF CANCER CLASSIFICATION

AN ENHANCED GAGS BASED MTSVSL LEARNING TECHNIQUE FOR CANCER MOLECULAR PATTERN PREDICTION OF CANCER CLASSIFICATION www.arpapress.com/volumes/vol8issue2/ijrras_8_2_02.pdf AN ENHANCED GAGS BASED MTSVSL LEARNING TECHNIQUE FOR CANCER MOLECULAR PATTERN PREDICTION OF CANCER CLASSIFICATION I. Jule 1 & E. Krubakaran 2 1 Department

More information

Biomarker Selection from Gene Expression Data for Tumour Categorization Using Bat Algorithm

Biomarker Selection from Gene Expression Data for Tumour Categorization Using Bat Algorithm Receved: March 20, 2017 401 Bomarker Selecton from Gene Expresson Data for Tumour Categorzaton Usng Bat Algorthm Gunavath Chellamuthu 1 *, Premalatha Kandasamy 2, Svasubramanan Kanagaraj 3 1 School of

More information

A MIXTURE OF EXPERTS FOR CATARACT DIAGNOSIS IN HOSPITAL SCREENING DATA

A MIXTURE OF EXPERTS FOR CATARACT DIAGNOSIS IN HOSPITAL SCREENING DATA Journal of Theoretcal and Appled Informaton Technology 2005 ongong JATIT & LLS ISSN: 1992-8645 www.jatt.org E-ISSN: 1817-3195 A MIXTURE OF EXPERTS FOR CATARACT DIAGNOSIS IN HOSPITAL SCREENING DATA 1 SUNGMIN

More information

Modeling the Survival of Retrospective Clinical Data from Prostate Cancer Patients in Komfo Anokye Teaching Hospital, Ghana

Modeling the Survival of Retrospective Clinical Data from Prostate Cancer Patients in Komfo Anokye Teaching Hospital, Ghana Internatonal Journal of Appled Scence and Technology Vol. 5, No. 6; December 2015 Modelng the Survval of Retrospectve Clncal Data from Prostate Cancer Patents n Komfo Anokye Teachng Hosptal, Ghana Asedu-Addo,

More information

Using Past Queries for Resource Selection in Distributed Information Retrieval

Using Past Queries for Resource Selection in Distributed Information Retrieval Purdue Unversty Purdue e-pubs Department of Computer Scence Techncal Reports Department of Computer Scence 2011 Usng Past Queres for Resource Selecton n Dstrbuted Informaton Retreval Sulleyman Cetntas

More information

Adaptive Neuro Fuzzy Inference System (ANFIS): MATLAB Simulation of Breast Cancer Experimental Data

Adaptive Neuro Fuzzy Inference System (ANFIS): MATLAB Simulation of Breast Cancer Experimental Data IOSR Journal of Computer Engneerng (IOSR-JCE) e-issn: 2278-0661,p-ISSN: 2278-8727, Volume 19, Issue 4, Ver. V. (Jul.-Aug. 2017), PP 53-60 www.osrjournals.org Adaptve Neuro Fuzzy Inference System (ANFIS):

More information

Modeling Multi Layer Feed-forward Neural. Network Model on the Influence of Hypertension. and Diabetes Mellitus on Family History of

Modeling Multi Layer Feed-forward Neural. Network Model on the Influence of Hypertension. and Diabetes Mellitus on Family History of Appled Mathematcal Scences, Vol. 7, 2013, no. 41, 2047-2053 HIKARI Ltd, www.m-hkar.com Modelng Mult Layer Feed-forward Neural Network Model on the Influence of Hypertenson and Dabetes Melltus on Famly

More information

Prediction of Human Disease-Related Gene Clusters by Clustering Analysis

Prediction of Human Disease-Related Gene Clusters by Clustering Analysis Int. J. Bol. Sc. 2011, 7 61 Research Paper Internatonal Journal of Bologcal Scences 2011; 7(1):61-73 Ivysprng Internatonal Publsher. All rghts reserved Predcton of Human Dsease-Related Gene Clusters by

More information

Physical Model for the Evolution of the Genetic Code

Physical Model for the Evolution of the Genetic Code Physcal Model for the Evoluton of the Genetc Code Tatsuro Yamashta Osamu Narkyo Department of Physcs, Kyushu Unversty, Fukuoka 8-856, Japan Abstract We propose a physcal model to descrbe the mechansms

More information

A Computer-aided System for Discriminating Normal from Cancerous Regions in IHC Liver Cancer Tissue Images Using K-means Clustering*

A Computer-aided System for Discriminating Normal from Cancerous Regions in IHC Liver Cancer Tissue Images Using K-means Clustering* A Computer-aded System for Dscrmnatng Normal from Cancerous Regons n IHC Lver Cancer Tssue Images Usng K-means Clusterng* R. M. CHEN 1, Y. J. WU, S. R. JHUANG, M. H. HSIEH, C. L. KUO, Y. L. MA Department

More information

Insights in Genetics and Genomics

Insights in Genetics and Genomics Insghts n Genetcs and Genomcs Research Artcle Open Access New Score Tests for Equalty of Varances n the Applcaton of DNA Methylaton Data Analyss [Verson ] Welang Qu Xuan L Jarrett Morrow Dawn L DeMeo Scott

More information

A GEOGRAPHICAL AND STATISTICAL ANALYSIS OF LEUKEMIA DEATHS RELATING TO NUCLEAR POWER PLANTS. Whitney Thompson, Sarah McGinnis, Darius McDaniel,

A GEOGRAPHICAL AND STATISTICAL ANALYSIS OF LEUKEMIA DEATHS RELATING TO NUCLEAR POWER PLANTS. Whitney Thompson, Sarah McGinnis, Darius McDaniel, A GEOGRAPHICAL AD STATISTICAL AALYSIS OF LEUKEMIA DEATHS RELATIG TO UCLEAR POWER PLATS Whtney Thompson, Sarah McGnns, Darus McDanel, Jean Sexton, Rebecca Pettt, Sarah Anderson, Monca Jackson ABSTRACT:

More information

Lymphoma Cancer Classification Using Genetic Programming with SNR Features

Lymphoma Cancer Classification Using Genetic Programming with SNR Features Lymphoma Cancer Classfcaton Usng Genetc Programmng wth SNR Features Jn-Hyuk Hong and Sung-Bae Cho Dept. of Computer Scence, Yonse Unversty, 134 Shnchon-dong, Sudaemoon-ku, Seoul 120-749, Korea hjnh@candy.yonse.ac.kr,

More information

Statistically Weighted Voting Analysis of Microarrays for Molecular Pattern Selection and Discovery Cancer Genotypes

Statistically Weighted Voting Analysis of Microarrays for Molecular Pattern Selection and Discovery Cancer Genotypes IJCSNS Internatonal Journal of Computer Scence and Network Securty, VOL.6 No.2, December 26 73 Statstcally Weghted Votng Analyss of Mcroarrays for Molecular Pattern Selecton and Dscovery Cancer Genotypes

More information

Integrative Computational Identifications of the Signaling Pathway Network Related to TNF-alpha Stimulus in Vascular Endothelial Cells

Integrative Computational Identifications of the Signaling Pathway Network Related to TNF-alpha Stimulus in Vascular Endothelial Cells Integratve Computatonal Identfcatons of the Sgnalng Pathway Network Related to -alpha Stmulus n Vascular Endothelal Cells Jn Gu, Shao L, Yang Chen, Yanda L MOE Key Laboratory of Bonformatcs and Bonformatcs

More information

Estimation for Pavement Performance Curve based on Kyoto Model : A Case Study for Highway in the State of Sao Paulo

Estimation for Pavement Performance Curve based on Kyoto Model : A Case Study for Highway in the State of Sao Paulo Estmaton for Pavement Performance Curve based on Kyoto Model : A Case Study for Kazuya AOKI, PASCO CORPORATION, Yokohama, JAPAN, Emal : kakzo603@pasco.co.jp Octávo de Souza Campos, Publc Servces Regulatory

More information

Incorporating prior biological knowledge for network-based differential gene expression analysis using differentially weighted graphical LASSO

Incorporating prior biological knowledge for network-based differential gene expression analysis using differentially weighted graphical LASSO Zuo et al. BMC Bonformatcs (2017) 18:99 DOI 10.1186/s12859-017-1515-1 METHODOLOGY ARTICLE Open Access Incorporatng pror bologcal knowledge for network-based dfferental gene expresson analyss usng dfferentally

More information

Unobserved Heterogeneity and the Statistical Analysis of Highway Accident Data

Unobserved Heterogeneity and the Statistical Analysis of Highway Accident Data Unobserved Heterogenety and the Statstcal Analyss of Hghway Accdent Data Fred L. Mannerng Professor of Cvl and Envronmental Engneerng Courtesy Department of Economcs Unversty of South Florda 4202 E. Fowler

More information

Evaluation of the generalized gamma as a tool for treatment planning optimization

Evaluation of the generalized gamma as a tool for treatment planning optimization Internatonal Journal of Cancer Therapy and Oncology www.jcto.org Evaluaton of the generalzed gamma as a tool for treatment plannng optmzaton Emmanoul I Petrou 1,, Ganesh Narayanasamy 3, Eleftheros Lavdas

More information

An Approach to Discover Dependencies between Service Operations*

An Approach to Discover Dependencies between Service Operations* 36 JOURNAL OF SOFTWARE VOL. 3 NO. 9 DECEMBER 2008 An Approach to Dscover Dependences between Servce Operatons* Shuyng Yan Research Center for Grd and Servce Computng Insttute of Computng Technology Chnese

More information

(From the Gastroenterology Division, Cornell University Medical College, New York 10021)

(From the Gastroenterology Division, Cornell University Medical College, New York 10021) ROLE OF HEPATIC ANION-BINDING PROTEIN IN BROMSULPHTHALEIN CONJUGATION* BY N. KAPLOWITZ, I. W. PERC -ROBB,~ ANn N. B. JAVITT (From the Gastroenterology Dvson, Cornell Unversty Medcal College, New York 10021)

More information

Sparse Representation of HCP Grayordinate Data Reveals. Novel Functional Architecture of Cerebral Cortex

Sparse Representation of HCP Grayordinate Data Reveals. Novel Functional Architecture of Cerebral Cortex 1 Sparse Representaton of HCP Grayordnate Data Reveals Novel Functonal Archtecture of Cerebral Cortex X Jang 1, Xang L 1, Jngle Lv 2,1, Tuo Zhang 2,1, Shu Zhang 1, Le Guo 2, Tanmng Lu 1* 1 Cortcal Archtecture

More information

Feature Selection for Predicting Tumor Metastases in Microarray Experiments using Paired Design

Feature Selection for Predicting Tumor Metastases in Microarray Experiments using Paired Design Feature Selecton for Predctng Tumor Metastases n Mcroarray Experments usng Pared Desgn Qhua Tan 1,2, Mads Thomassen 1 and Torben A. Kruse 1 ORIGINAL RESEARCH 1 Department of Bochemstry, Pharmacology and

More information

Evaluation of Literature-based Discovery Systems

Evaluation of Literature-based Discovery Systems Evaluaton of Lterature-based Dscovery Systems Melha Yetsgen-Yldz 1 and Wanda Pratt 1,2 1 The Informaton School, Unversty of Washngton, Seattle, USA. 2 Bomedcal and Health Informatcs, School of Medcne,

More information

Introduction ORIGINAL RESEARCH

Introduction ORIGINAL RESEARCH ORIGINAL RESEARCH Assessng the Statstcal Sgnfcance of the Acheved Classfcaton Error of Classfers Constructed usng Serum Peptde Profles, and a Prescrpton for Random Samplng Repeated Studes for Massve Hgh-Throughput

More information

Journal of Engineering Science and Technology Review 11 (2) (2018) Research Article

Journal of Engineering Science and Technology Review 11 (2) (2018) Research Article Jestr Journal of Engneerng Scence and Technology Revew () (08) 5 - Research Artcle Prognoss Evaluaton of Ovaran Granulosa Cell Tumor Based on Co-forest ntellgence Model Xn Lao Xn Zheng Juan Zou Mn Feng

More information

A Support Vector Machine Classifier based on Recursive Feature Elimination for Microarray Data in Breast Cancer Characterization. Abstract.

A Support Vector Machine Classifier based on Recursive Feature Elimination for Microarray Data in Breast Cancer Characterization. Abstract. A Support Vector Machne Classfer based on Recursve Feature Elmnaton for Mcroarray Data n Breast Cancer Characterzaton. R.Campann, D. Dongovann, E. Iamper, N. Lanconell, G. Palermo, M. Roffll, A. Rccard

More information

Price linkages in value chains: methodology

Price linkages in value chains: methodology Prce lnkages n value chans: methodology Prof. Trond Bjorndal, CEMARE. Unversty of Portsmouth, UK. and Prof. José Fernández-Polanco Unversty of Cantabra, Span. FAO INFOSAMAK Tangers, Morocco 14 March 2012

More information

What Determines Attitude Improvements? Does Religiosity Help?

What Determines Attitude Improvements? Does Religiosity Help? Internatonal Journal of Busness and Socal Scence Vol. 4 No. 9; August 2013 What Determnes Atttude Improvements? Does Relgosty Help? Madhu S. Mohanty Calforna State Unversty-Los Angeles Los Angeles, 5151

More information

A New Machine Learning Algorithm for Breast and Pectoral Muscle Segmentation

A New Machine Learning Algorithm for Breast and Pectoral Muscle Segmentation Avalable onlne www.ejaet.com European Journal of Advances n Engneerng and Technology, 2015, 2(1): 21-29 Research Artcle ISSN: 2394-658X A New Machne Learnng Algorthm for Breast and Pectoral Muscle Segmentaton

More information

INITIAL ANALYSIS OF AWS-OBSERVED TEMPERATURE

INITIAL ANALYSIS OF AWS-OBSERVED TEMPERATURE INITIAL ANALYSIS OF AWS-OBSERVED TEMPERATURE Wang Yng, Lu Xaonng, Ren Zhhua, Natonal Meteorologcal Informaton Center, Bejng, Chna Tel.:+86 684755, E-mal:cdcsjk@cma.gov.cn Abstract From, n Chna meteorologcal

More information

*VALLIAPPAN Raman 1, PUTRA Sumari 2 and MANDAVA Rajeswari 3. George town, Penang 11800, Malaysia. George town, Penang 11800, Malaysia

*VALLIAPPAN Raman 1, PUTRA Sumari 2 and MANDAVA Rajeswari 3. George town, Penang 11800, Malaysia. George town, Penang 11800, Malaysia 38 A Theoretcal Methodology and Prototype Implementaton for Detecton Segmentaton Classfcaton of Dgtal Mammogram Tumor by Machne Learnng and Problem Solvng *VALLIAPPA Raman, PUTRA Sumar 2 and MADAVA Rajeswar

More information

ALMALAUREA WORKING PAPERS no. 9

ALMALAUREA WORKING PAPERS no. 9 Snce 1994 Inter-Unversty Consortum Connectng Unverstes, the Labour Market and Professonals AlmaLaurea Workng Papers ISSN 2239-9453 ALMALAUREA WORKING PAPERS no. 9 September 211 Propensty Score Methods

More information

A Support Vector Machine Classifier based on Recursive Feature Elimination for Microarray Data in Breast Cancer Characterization. Abstract.

A Support Vector Machine Classifier based on Recursive Feature Elimination for Microarray Data in Breast Cancer Characterization. Abstract. A Support Vector Machne Classfer based on Recursve Feature Elmnaton for Mcroarray Data n Breast Cancer Characterzaton. R.Campann, D. Dongovann, N. Lanconell, G. Palermo, A. Rccard, M. Roffll Dpartmento

More information

Fast Algorithm for Vectorcardiogram and Interbeat Intervals Analysis: Application for Premature Ventricular Contractions Classification

Fast Algorithm for Vectorcardiogram and Interbeat Intervals Analysis: Application for Premature Ventricular Contractions Classification Fast Algorthm for Vectorcardogram and Interbeat Intervals Analyss: Applcaton for Premature Ventrcular Contractons Classfcaton Irena Jekova, Vessela Krasteva Centre of Bomedcal Engneerng Prof. Ivan Daskalov

More information

Appendix for. Institutions and Behavior: Experimental Evidence on the Effects of Democracy

Appendix for. Institutions and Behavior: Experimental Evidence on the Effects of Democracy Appendx for Insttutons and Behavor: Expermental Evdence on the Effects of Democrac 1. Instructons 1.1 Orgnal sessons Welcome You are about to partcpate n a stud on decson-makng, and ou wll be pad for our

More information

The effect of salvage therapy on survival in a longitudinal study with treatment by indication

The effect of salvage therapy on survival in a longitudinal study with treatment by indication Research Artcle Receved 28 October 2009, Accepted 8 June 2010 Publshed onlne 30 August 2010 n Wley Onlne Lbrary (wleyonlnelbrary.com) DOI: 10.1002/sm.4017 The effect of salvage therapy on survval n a longtudnal

More information

RENAL FUNCTION AND ACE INHIBITORS IN RENAL ARTERY STENOSISA/adbon et al. 651

RENAL FUNCTION AND ACE INHIBITORS IN RENAL ARTERY STENOSISA/adbon et al. 651 Downloaded from http://ahajournals.org by on January, 209 RENAL FUNCTION AND INHIBITORS IN RENAL ARTERY STENOSISA/adbon et al. 65 Downloaded from http://ahajournals.org by on January, 209 Patents and Methods

More information

NUMERICAL COMPARISONS OF BIOASSAY METHODS IN ESTIMATING LC50 TIANHONG ZHOU

NUMERICAL COMPARISONS OF BIOASSAY METHODS IN ESTIMATING LC50 TIANHONG ZHOU NUMERICAL COMPARISONS OF BIOASSAY METHODS IN ESTIMATING LC50 by TIANHONG ZHOU B.S., Chna Agrcultural Unversty, 2003 M.S., Chna Agrcultural Unversty, 2006 A THESIS submtted n partal fulfllment of the requrements

More information

Optimal Planning of Charging Station for Phased Electric Vehicle *

Optimal Planning of Charging Station for Phased Electric Vehicle * Energy and Power Engneerng, 2013, 5, 1393-1397 do:10.4236/epe.2013.54b264 Publshed Onlne July 2013 (http://www.scrp.org/ournal/epe) Optmal Plannng of Chargng Staton for Phased Electrc Vehcle * Yang Gao,

More information

BIOSTATISTICS. Lecture 1 Data Presentation and Descriptive Statistics. dr. Petr Nazarov

BIOSTATISTICS. Lecture 1 Data Presentation and Descriptive Statistics. dr. Petr Nazarov Genomcs Research Unt BIOSTATISTICS Lecture 1 Data Presentaton and Descrptve Statstcs dr. Petr Nazarov 3-03-2017 petr.nazarov@lh.lu COURSE OVERVIEW Organzaton: 60h = 12 days Theoretcal course (30h) Theory

More information

Statistical Analysis on Infectious Diseases in Dubai, UAE

Statistical Analysis on Infectious Diseases in Dubai, UAE Internatonal Journal of Preventve Medcne Research Vol. 1, No. 4, 015, pp. 60-66 http://www.ascence.org/journal/jpmr Statstcal Analyss on Infectous Dseases 1995-013 n Duba, UAE Khams F. G. 1, Hussan H.

More information

BIOSTATISTICS. Lecture 1 Data Presentation and Descriptive Statistics. dr. Petr Nazarov

BIOSTATISTICS. Lecture 1 Data Presentation and Descriptive Statistics. dr. Petr Nazarov Mcroarray Center BIOSTATISTICS Lecture 1 Data Presentaton and Descrptve Statstcs dr. Petr Nazarov 22-02-2012 petr.nazarov@crp-sante.lu COURSE OVERVIEW Organzaton Theoretcal course (30h) Theory Explanatons

More information

Statistical models for predicting number of involved nodes in breast cancer patients

Statistical models for predicting number of involved nodes in breast cancer patients Vol.2, No.7, 641-651 (2010) do:10.4236/health.2010.27098 Health Statstcal models for predctng number of nvolved nodes n breast cancer patents Alok Kumar Dwved 1 *, Sada Nand Dwved 2, Suryanarayana Deo

More information

Association between cholesterol and cardiac parameters.

Association between cholesterol and cardiac parameters. Short communcaton http://www.alledacademes.org/cholesterol-and-heart-dsease/ Assocaton between cholesterol and cardac parameters. Rabndra Nath Das* Department of Statstcs, The Unversty of Burdwan, Burdwan,

More information

Effects of Estrogen Contamination on Human Cells: Modeling and Prediction Based on Michaelis-Menten Kinetics 1

Effects of Estrogen Contamination on Human Cells: Modeling and Prediction Based on Michaelis-Menten Kinetics 1 J. Water Resource and Protecton, 009,, 6- do:0.6/warp.009.500 Publshed Onlne ovember 009 (http://www.scrp.org/ournal/warp) Effects of Estrogen Contamnaton on Human Cells: Modelng and Predcton Based on

More information

Maize Varieties Combination Model of Multi-factor. and Implement

Maize Varieties Combination Model of Multi-factor. and Implement Maze Varetes Combnaton Model of Mult-factor and Implement LIN YANG,XIAODONG ZHANG,SHAOMING LI Department of Geographc Informaton Scence Chna Agrcultural Unversty No. 17 Tsnghua East Road, Bejng 100083

More information

Research Article Statistical Analysis of Haralick Texture Features to Discriminate Lung Abnormalities

Research Article Statistical Analysis of Haralick Texture Features to Discriminate Lung Abnormalities Hndaw Publshng Corporaton Internatonal Journal of Bomedcal Imagng Volume 2015, Artcle ID 267807, 7 pages http://dx.do.org/10.1155/2015/267807 Research Artcle Statstcal Analyss of Haralck Texture Features

More information

A comparison of statistical methods in interrupted time series analysis to estimate an intervention effect

A comparison of statistical methods in interrupted time series analysis to estimate an intervention effect Peer revew stream A comparson of statstcal methods n nterrupted tme seres analyss to estmate an nterventon effect a,b, J.J.J., Walter c, S., Grzebeta a, R. & Olver b, J. a Transport and Road Safety, Unversty

More information

Tumor Phylogenetic Lineage Separation by Medoidshift Clustering with Non-Positive Kernel

Tumor Phylogenetic Lineage Separation by Medoidshift Clustering with Non-Positive Kernel Tumor Phylogenetc Lneage Separaton by Medodshft Clusterng wth Non-Postve Kernel Lu Xe School of Computer Scence Carnege Mellon Unversty Pttsburgh, PA 15213 lxe1@andrew.cmu.edu Commttee Dr. Russell Schwartz,

More information

An Improved Time Domain Pitch Detection Algorithm for Pathological Voice

An Improved Time Domain Pitch Detection Algorithm for Pathological Voice Amercan Journal of Appled Scences 9 (1): 93-102, 2012 ISSN 1546-9239 2012 Scence Publcatons An Improved Tme Doman Ptch Detecton Algorthm for Pathologcal Voce Mohd Redzuan Jamaludn, Shekh Hussan Shakh Salleh,

More information

AUTOMATED DETECTION OF HARD EXUDATES IN FUNDUS IMAGES USING IMPROVED OTSU THRESHOLDING AND SVM

AUTOMATED DETECTION OF HARD EXUDATES IN FUNDUS IMAGES USING IMPROVED OTSU THRESHOLDING AND SVM AUTOMATED DETECTION OF HARD EXUDATES IN FUNDUS IMAGES USING IMPROVED OTSU THRESHOLDING AND SVM Wewe Gao 1 and Jng Zuo 2 1 College of Mechancal Engneerng, Shangha Unversty of Engneerng Scence, Shangha,

More information

Latent Class Analysis for Marketing Scales Development

Latent Class Analysis for Marketing Scales Development Workng Paper Seres, N.16, 2009 Latent Class Analyss for Marketng Scales Development Francesca Bass Department of Statstcal Scences Unversty of Padua Italy Abstract: Measurement scales are a crucal nstrument

More information

Mathematical model of fish schooling behaviour in a set-net

Mathematical model of fish schooling behaviour in a set-net ICES Journal of Marne Scence, 61: 114e13 (004) do:10.1016/j.cesjms.004.07.009 Mathematcal model of fsh schoolng behavour n a set-net Tsutomu Takag, Yutaka Mortom, Jyun Iwata, Hrosh Nakamne, and Nobuo Sannomya

More information

HYPEIIGLTCAEMIA AS A MENDELIAN P~ECESSIVE CHAI~ACTEP~ IN MICE.

HYPEIIGLTCAEMIA AS A MENDELIAN P~ECESSIVE CHAI~ACTEP~ IN MICE. HYPEGLTCAEMA AS A MENDELAN P~ECESSVE CHA~ACTEP~ N MCE. BY P. J. CAM~CDGE, M.D. (LEND.), 32 Nottngham Place, Ma~'y~ebone, London, W, 1, AND H. A. H. {OWAZD, B.So. (Lol, m.). h'~ the course of an nvestgaton

More information

EVALUATION OF BULK MODULUS AND RING DIAMETER OF SOME TELLURITE GLASS SYSTEMS

EVALUATION OF BULK MODULUS AND RING DIAMETER OF SOME TELLURITE GLASS SYSTEMS Chalcogende Letters Vol. 12, No. 2, February 2015, p. 67-74 EVALUATION OF BULK MODULUS AND RING DIAMETER OF SOME TELLURITE GLASS SYSTEMS R. EL-MALLAWANY a*, M.S. GAAFAR b, N. VEERAIAH c a Physcs Dept.,

More information

STAGE-STRUCTURED POPULATION DYNAMICS OF AEDES AEGYPTI

STAGE-STRUCTURED POPULATION DYNAMICS OF AEDES AEGYPTI Internatonal Conference Mathematcal and Computatonal Bology 211 Internatonal Journal of Modern Physcs: Conference Seres Vol. 9 (212) 364 372 World Scentfc Publshng Company DOI: 1.1142/S21194512543 STAGE-STRUCTURED

More information

Concentration of teicoplanin in the serum of adults with end stage chronic renal failure undergoing treatment for infection

Concentration of teicoplanin in the serum of adults with end stage chronic renal failure undergoing treatment for infection Journal of Antmcrobal Chemotherapy (1996) 37, 117-121 Concentraton of tecoplann n the serum of adults wth end stage chronc renal falure undergong treatment for nfecton A. MercateUo'*, K. Jaber*, D. Hfflare-Buys*,

More information

Estimation of Relative Survival Based on Cancer Registry Data

Estimation of Relative Survival Based on Cancer Registry Data Revew of Bonformatcs and Bometrcs (RBB) Volume 2 Issue 4, December 203 www.sepub.org/rbb Estmaton of Relatve Based on Cancer Regstry Data Olaf Schoffer *, Ante Nedostate 2, Stefane J. Klug,2 Cancer Epdemology,

More information

Research Article Computational Analysis of Specific MicroRNA Biomarkers for Noninvasive Early Cancer Detection

Research Article Computational Analysis of Specific MicroRNA Biomarkers for Noninvasive Early Cancer Detection Hndaw BoMed Research Internatonal Volume 0, Artcle ID 00, pages https://do.org/0./0/00 Research Artcle Computatonal Analyss of Specfc McroRNA Bomarkers for Nonnvasve Early Detecton Tanc Song, Yanchun Lang,,

More information

Balanced Query Methods for Improving OCR-Based Retrieval

Balanced Query Methods for Improving OCR-Based Retrieval Balanced Query Methods for Improvng OCR-Based Retreval Kareem Darwsh Electrcal and Computer Engneerng Dept. Unversty of Maryland, College Park College Park, MD 20742 kareem@glue.umd.edu Douglas W. Oard

More information

Title: Life Tables of Bactrocera cucurbitae (Coquillett) (Diptera: Tephritidae):

Title: Life Tables of Bactrocera cucurbitae (Coquillett) (Diptera: Tephritidae): Page 1 of 31 1 2 3 Ttle: Lfe Tables of Bactrocera cucurbtae (Coqullett) (Dptera: Tephrtdae): wth a Mathematcal Invaldaton for Applyng the Jackknfe Technque to the Net Reproductve Rate 4 5 Runnng ttle:

More information

FAST DETECTION OF MASSES IN MAMMOGRAMS WITH DIFFICULT CASE EXCLUSION

FAST DETECTION OF MASSES IN MAMMOGRAMS WITH DIFFICULT CASE EXCLUSION computng@tanet.edu.te.ua www.tanet.edu.te.ua/computng ISSN 727-6209 Internatonal Scentfc Journal of Computng FAST DETECTION OF MASSES IN MAMMOGRAMS WITH DIFFICULT CASE EXCLUSION Gábor Takács ), Béla Patak

More information

Available online at ScienceDirect. Procedia Computer Science 46 (2015 )

Available online at   ScienceDirect. Procedia Computer Science 46 (2015 ) Avalable onlne at www.scencedrect.com ScenceDrect Proceda Computer Scence 46 (215 ) 1762 1769 Internatonal Conference on Informaton and Communcaton Technologes (ICICT 214) Automatc Characterzaton of Bengn

More information

ARTICLE IN PRESS Biomedical Signal Processing and Control xxx (2011) xxx xxx

ARTICLE IN PRESS Biomedical Signal Processing and Control xxx (2011) xxx xxx Bomedcal Sgnal Processng and Control xxx (2011) xxx xxx Contents lsts avalable at ScenceDrect Bomedcal Sgnal Processng and Control journa l h omepage: www.elsever.com/locate/bspc Dscovery of multple level

More information

The Effect of Fish Farmers Association on Technical Efficiency: An Application of Propensity Score Matching Analysis

The Effect of Fish Farmers Association on Technical Efficiency: An Application of Propensity Score Matching Analysis The Effect of Fsh Farmers Assocaton on Techncal Effcency: An Applcaton of Propensty Score Matchng Analyss Onumah E. E, Esslfe F. L, and Asumng-Brempong, S 15 th July, 2016 Background and Motvaton Outlne

More information

Validation of the Gravity Model in Predicting the Global Spread of Influenza

Validation of the Gravity Model in Predicting the Global Spread of Influenza Int. J. Envron. Res. Publc Health 2011, 8, 3134-3143; do:10.3390/jerph8083134 OPEN ACCESS Internatonal Journal of Envronmental Research and Publc Health ISSN 1660-4601 www.mdp.com/journal/jerph Artcle

More information

ADDITIVE MAIN EFFECTS AND MULTIPLICATIVE INTERACTION (AMMI) ANALYSIS OF GRAIN YIELD STABILITY IN EARLY DURATION RICE ABSTRACT

ADDITIVE MAIN EFFECTS AND MULTIPLICATIVE INTERACTION (AMMI) ANALYSIS OF GRAIN YIELD STABILITY IN EARLY DURATION RICE ABSTRACT Bose et al., The Journal of Anmal & Plant Scences, 4(6): 014, Page: J. 1885-1897 Anm. Plant Sc. 4(6):014 ISSN: 1018-7081 ADDITIVE MAIN EFFECTS AND MULTIPLICATIVE INTERACTION (AMMI) ANALYSIS OF GRAIN YIELD

More information

CLUSTERING is always popular in modern technology

CLUSTERING is always popular in modern technology Max-Entropy Feed-Forward Clusterng Neural Network Han Xao, Xaoyan Zhu arxv:1506.03623v1 [cs.lg] 11 Jun 2015 Abstract The outputs of non-lnear feed-forward neural network are postve, whch could be treated

More information

Improvement of Automatic Hemorrhages Detection Methods using Brightness Correction on Fundus Images

Improvement of Automatic Hemorrhages Detection Methods using Brightness Correction on Fundus Images Improvement of Automatc Hemorrhages Detecton Methods usng Brghtness Correcton on Fundus Images Yuj Hatanaka *a, Toshak Nakagawa *b, Yoshnor Hayash *c, Masakatsu Kakogawa *c, Akra Sawada *d, Kazuhde Kawase

More information

Towards Prediction of Radiation Pneumonitis Arising from Lung Cancer Patients Using Machine Learning Approaches

Towards Prediction of Radiation Pneumonitis Arising from Lung Cancer Patients Using Machine Learning Approaches Towards Predcton of Radaton Pneumonts Arsng from Lung Cancer Patents Usng Machne Learnng Approaches Jung Hun Oh, Adtya Apte, Rawan Al-Loz, Jeffrey Bradley, Issam El Naqa * Dvson of Bonformatcs and Outcomes

More information

Subject-Adaptive Real-Time Sleep Stage Classification Based on Conditional Random Field

Subject-Adaptive Real-Time Sleep Stage Classification Based on Conditional Random Field Subject-Adaptve Real-Tme Sleep Stage Classfcaton Based on Condtonal Random Feld Gang Luo, PhD, Wanl Mn, PhD IBM TJ Watson Research Center, Hawthorne, NY {luog, wanlmn}@usbmcom Abstract Sleep stagng s the

More information

Towards Automated Pose Invariant 3D Dental Biometrics

Towards Automated Pose Invariant 3D Dental Biometrics Towards Automated Pose Invarant 3D Dental Bometrcs Xn ZHONG 1, Depng YU 1, Kelvn W C FOONG, Terence SIM 3, Yoke San WONG 1 and Ho-lun CHENG 3 1. Mechancal Engneerng, Natonal Unversty of Sngapore, 117576,

More information

A SIMULATION STUDY OF MECHANISM OF POSTFLIGHT ORTHOSTATIC INTOLERANCE

A SIMULATION STUDY OF MECHANISM OF POSTFLIGHT ORTHOSTATIC INTOLERANCE Proceedngs 3rd Annual Conference IEEE/EMBS Oct.5-8, 001, Istanbul, TURKEY A SIMULATION STUDY OF MECHANISM OF POSTFLIGHT ORTHOSTATIC INTOLERANCE W. Y HAO 1, J. BAI 1, W. Y. ZHANG, X. Y. WU 3 L. F. ZHANG

More information

WHO S ASSESSMENT OF HEALTH CARE INDUSTRY PERFORMANCE: RATING THE RANKINGS

WHO S ASSESSMENT OF HEALTH CARE INDUSTRY PERFORMANCE: RATING THE RANKINGS WHO S ASSESSMENT OF HEALTH CARE INDUSTRY PERFORMANCE: RATING THE RANKINGS ELLIOTT PARKER and JEANNE WENDEL * Department of Economcs, Unversty of Nevada, Reno, NV, USA SUMMARY Ths paper examnes the econometrc

More information

Normal variation in the length of the luteal phase of the menstrual cycle: identification of the short luteal phase

Normal variation in the length of the luteal phase of the menstrual cycle: identification of the short luteal phase Brtsh Journal of Obstetrcs and Gvnaecologjl July 1984, Vol. 9 1, pp. 685-689 Normal varaton n the length of the luteal phase of the menstrual cycle: dentfcaton of the short luteal phase ELIZABETH A. LENTON,

More information

Multidimensional Reliability of Instrument for Measuring Students Attitudes Toward Statistics by Using Semantic Differential Scale

Multidimensional Reliability of Instrument for Measuring Students Attitudes Toward Statistics by Using Semantic Differential Scale Amercan Journal of Educatonal Research, 05, Vol. 3, No., 49-53 Avalable onlne at http://pubs.scepub.com/educaton/3//0 Scence and Educaton Publshng DOI:0.69/educaton-3--0 Multdmensonal Relablty of Instrument

More information

The Influence of the Isomerization Reactions on the Soybean Oil Hydrogenation Process

The Influence of the Isomerization Reactions on the Soybean Oil Hydrogenation Process Unversty of Belgrade From the SelectedWorks of Zeljko D Cupc 2000 The Influence of the Isomerzaton Reactons on the Soybean Ol Hydrogenaton Process Zeljko D Cupc, Insttute of Chemstry, Technology and Metallurgy

More information

Integration of sensory information within touch and across modalities

Integration of sensory information within touch and across modalities Integraton of sensory nformaton wthn touch and across modaltes Marc O. Ernst, Jean-Perre Brescan, Knut Drewng & Henrch H. Bülthoff Max Planck Insttute for Bologcal Cybernetcs 72076 Tübngen, Germany marc.ernst@tuebngen.mpg.de

More information

Leukemia in Polycythemia Vera. Relationship to Splenic Myeloid Metaplasia and Therapeutic Radiation Dose

Leukemia in Polycythemia Vera. Relationship to Splenic Myeloid Metaplasia and Therapeutic Radiation Dose Leukema n Polycythema Vera Relatonshp to Splenc Myelod Metaplasa and Therapeutc Radaton Dose JOHN H. LAWRENCE, M.D., D.SC, F.A.C.P., H. S. WINCHELL, M.D., PH.D., F.A.CP., and W. G. DONALD, M.D., F.A.C.P.

More information

Disease Mapping for Stomach Cancer in Libya Based on Besag York Mollié (BYM) Model

Disease Mapping for Stomach Cancer in Libya Based on Besag York Mollié (BYM) Model DI:0.034/APJCP.07.8.6.479 Dsease Mappng for Stomach Cancer n Lbya: Bayesan Study RESEARC ARTICLE Dsease Mappng for Stomach Cancer n Lbya Based on Besag York Mollé (BYM) Model Maryam Ahmed Salem Alhdr *,

More information

Incorrect Beliefs. Overconfidence. Types of Overconfidence. Outline. Overprecision 4/22/2015. Econ 1820: Behavioral Economics Mark Dean Spring 2015

Incorrect Beliefs. Overconfidence. Types of Overconfidence. Outline. Overprecision 4/22/2015. Econ 1820: Behavioral Economics Mark Dean Spring 2015 Incorrect Belefs Overconfdence Econ 1820: Behavoral Economcs Mark Dean Sprng 2015 In objectve EU we assumed that everyone agreed on what the probabltes of dfferent events were In subjectve expected utlty

More information

NHS Outcomes Framework

NHS Outcomes Framework NHS Outcomes Framework Doman 1 Preventng people from dyng prematurely Indcator Specfcatons Verson: 1.21 Date: May 2018 Author: Clncal Indcators Team NHS Outcomes Framework: Doman 1 Preventng people from

More information

A Linear Regression Model to Detect User Emotion for Touch Input Interactive Systems

A Linear Regression Model to Detect User Emotion for Touch Input Interactive Systems 2015 Internatonal Conference on Affectve Computng and Intellgent Interacton (ACII) A Lnear Regresson Model to Detect User Emoton for Touch Input Interactve Systems Samt Bhattacharya Dept of Computer Scence

More information