Vasant G Honavar

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Drena DobbsUniversity Professor, Emerita, Genetics, Development & Cell Biology, Iowa State UniversityVerified email at iastate.edu
Doina CarageaKansas State UniversityVerified email at ksu.edu
Jihoon YangSogang UniversityVerified email at sogang.ac.kr
Yasser EL-ManzalawyGeisinger Health SystemVerified email at geisinger.edu
Jie BaoMemectVerified email at memect.co
Jyotishman PathakCornell UniversityVerified email at med.cornell.edu
Samik BasuProfessor of Computer Science, Iowa State UniversityVerified email at iastate.edu
Changhui YanAssociate Professor, Department of Computer Science, North Dakota State UniversityVerified email at ndsu.edu
Cornelia CarageaUniversity of Illinois at ChicagoVerified email at uic.edu
Robert JerniganCurtiss Distinguished Professor in Biochemistry, Biophysics & Molecular Biology, Iowa StateVerified email at iastate.edu
Guy HelmerProfessor of Practice, Ivy College of Business, Iowa State UniversityVerified email at iastate.edu
Li C XueRadboud University Medical CenterVerified email at radboudumc.nl
Dae-Ki KangDongseo universityVerified email at dongseo.ac.kr
Yiwei SunCoupangVerified email at psu.edu
Tsung-Yu HsiehPennsylvania State UniversityVerified email at psu.edu
Carson AndorfComputational Biologist, USDA-ARSVerified email at iastate.edu
Fadi TowficPrometheus BiosciencesVerified email at prometheusbiosciences.com
Robyn LutzIowa State UniversityVerified email at iastate.edu
Sanghack LeeSeoul National UniversityVerified email at snu.ac.kr
Robi PolikarProfessor of Electrical and Computer Engineering, Rowan University, Glassboro, NJ, USAVerified email at rowan.edu

Vasant G Honavar

Dorothy Foehr Huck and J. Lloyd Huck Chair in Biomedical Data Sciences and Artificial Intelligence

Verified email at psu.edu - Homepage

Artificial Intelligence Machine Learning Data Science Bioinformatics Knowledge Representation


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Feature subset selection using a genetic algorithm J Yang, V Honavar IEEE Intelligent Systems and their Applications 13 (2), 44-49, 1998	2095	1998
Learn++: An incremental learning algorithm for supervised neural networks R Polikar, L Upda, SS Upda, V Honavar IEEE transactions on systems, man, and cybernetics, part C (applications and …, 2001	1156	2001
Mobile health technology evaluation: the mHealth evidence workshop S Kumar, WJ Nilsen, A Abernethy, A Atienza, K Patrick, M Pavel, WT Riley, ... American journal of preventive medicine 45 (2), 228-236, 2013	1081	2013
Predicting linear B‐cell epitopes using string kernels Y EL‐Manzalawy, D Dobbs, V Honavar Journal of Molecular Recognition: An Interdisciplinary Journal 21 (4), 243-255, 2008	785	2008
Predicting RNA-protein interactions using only sequence information UK Muppirala, VG Honavar, D Dobbs BMC bioinformatics 12 (1), 1-11, 2011	440	2011
Constructive neural-network learning algorithms for pattern classification R Parekh, J Yang, V Honavar IEEE Transactions on neural networks 11 (2), 436-451, 2000	373*	2000
Learning classifiers for misuse and anomaly detection using a bag of system calls representation DK Kang, D Fuller, V Honavar Proceedings from the Sixth Annual IEEE SMC Information Assurance Workshop …, 2005	274*	2005
Intelligent agents for intrusion detection GG Helmer, JSK Wong, V Honavar, L Miller 1998 IEEE Information Technology Conference, Information Environment for the …, 1998	246	1998
Predicting flexible length linear B-cell epitopes Y El-Manzalawy, D Dobbs, V Honavar Computational Systems Bioinformatics: (Volume 7), 121-132, 2008	244	2008
Lightweight agents for intrusion detection G Helmer, JSK Wong, V Honavar, L Miller, Y Wang Journal of systems and Software 67 (2), 109-122, 2003	231	2003
RNABindR: a server for analyzing and predicting RNA-binding sites in proteins M Terribilini, JD Sander, JH Lee, P Zaback, RL Jernigan, V Honavar, ... Nucleic acids research 35 (suppl_2), W578-W584, 2007	225	2007
Prediction of RNA binding sites in proteins from amino acid sequence M Terribilini, JH Lee, C Yan, RL Jernigan, V Honavar, D Dobbs Rna 12 (8), 1450-1462, 2006	220	2006
Glycosylation site prediction using ensembles of Support Vector Machine classifiers C Caragea, J Sinapov, A Silvescu, D Dobbs, V Honavar BMC bioinformatics 8, 1-13, 2007	215	2007
Recent advances in B-cell epitope prediction methods Y El-Manzalawy, V Honavar Immunome research 6, 1-9, 2010	213	2010
A two-stage classifier for identification of protein–protein interface residues C Yan, D Dobbs, V Honavar Bioinformatics 20 (suppl_1), i371-i378, 2004	199	2004
Characterization of protein–protein interfaces C Yan, F Wu, RL Jernigan, D Dobbs, V Honavar The protein journal 27, 59-70, 2008	196	2008
A software fault tree approach to requirements analysis of an intrusion detection system G Helmer, J Wong, M Slagell, V Honavar, L Miller, R Lutz Requirements Engineering 7, 207-220, 2002	190	2002
Predicting DNA-binding sites of proteins from amino acid sequence C Yan, M Terribilini, F Wu, RL Jernigan, D Dobbs, V Honavar BMC bioinformatics 7, 1-10, 2006	177	2006
Computational prediction of protein interfaces: A review of data driven methods LC Xue, D Dobbs, AMJJ Bonvin, V Honavar FEBS letters 589 (23), 3516-3526, 2015	174	2015
WLSVM: integrating LibSVM into Weka environment Y El-Manzalawy, V Honavar Software available at http://www. cs. iastate. edu/yasser/wlsvm, 2005	173	2005

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