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
Yasser EL-ManzalawyGeisinger Health SystemVerified email at geisinger.edu
Jihoon YangSogang UniversityVerified email at sogang.ac.kr
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
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
Changhui YanAssociate Professor, Department of Computer Science, North Dakota State UniversityVerified email at ndsu.edu
Li C XueRadboud University Medical CenterVerified email at radboudumc.nl
Yiwei SunMetaVerified email at psu.edu
Guy HelmerProfessor of Practice, Ivy College of Business, Iowa State UniversityVerified email at iastate.edu
Dae-Ki KangDongseo universityVerified email at dongseo.ac.kr
Tsung-Yu HsiehPennsylvania State UniversityVerified email at psu.edu
Carson AndorfComputational Biologist, USDA-ARSVerified email at iastate.edu
Suhang WangPennsylvania State UniversityVerified email at psu.edu
Sanghack LeeSeoul National UniversityVerified email at snu.ac.kr
Fadi TowficPrometheus BiosciencesVerified email at prometheusbiosciences.com
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	2175	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	1207	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	1193	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	835	2008
Predicting RNA-protein interactions using only sequence information UK Muppirala, VG Honavar, D Dobbs BMC bioinformatics 12, 1-11, 2011	498	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	388*	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	276*	2005
Predicting flexible length linear B-cell epitopes ELM Yasser, D Dobbs, V Honavar Computational systems bioinformatics 7, 121, 2008	259	2008
Intelligent agents for intrusion detection GG Helmer, JSK Wong, V Honavar, L Miller 1998 IEEE Information Technology Conference, Information Environment for the …, 1998	250	1998
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	228	2007
Recent advances in B-cell epitope prediction methods Y El-Manzalawy, V Honavar Immunome research 6, 1-9, 2010	227	2010
Characterization of protein–protein interfaces C Yan, F Wu, RL Jernigan, D Dobbs, V Honavar The protein journal 27, 59-70, 2008	224	2008
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	222	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	218	2006
A two-stage classifier for identification of protein–protein interface residues C Yan, D Dobbs, V Honavar Bioinformatics 20 (suppl_1), i371-i378, 2004	201	2004
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	194	2015
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	188	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	179	2006
Adversarial attacks on graph neural networks via node injections: A hierarchical reinforcement learning approach Y Sun, S Wang, X Tang, TY Hsieh, V Honavar Proceedings of the Web Conference 2020, 673-683, 2020	174	2020

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