| AgBase: supporting functional modeling in agricultural organisms FM McCarthy, CR Gresham, TJ Buza, P Chouvarine, LR Pillai, R Kumar, ... Nucleic acids research 39 (suppl_1), D497-D506, 2011 | 83 | 2011 |
| The digital revolution in phenotyping A Oellrich, N Collier, T Groza, D Rebholz-Schuhmann, N Shah, ... Briefings in bioinformatics 17 (5), 819-830, 2016 | 64 | 2016 |
| Cross-ontology multi-level association rule mining in the gene ontology P Manda, S Ozkan, H Wang, F McCarthy, SM Bridges Public Library of Science 7 (10), e47411, 2012 | 47 | 2012 |
| Interestingness measures and strategies for mining multi-ontology multi-level association rules from gene ontology annotations for the discovery of new GO relationships P Manda, F McCarthy, SM Bridges Journal of biomedical informatics 46 (5), 849-856, 2013 | 43 | 2013 |
| Comparing gene annotation enrichment tools for functional modeling of agricultural microarray data BHJ Van den Berg, C Thanthiriwatte, P Manda, SM Bridges BMC bioinformatics 10 (11), 1-9, 2009 | 29 | 2009 |
| Using the phenoscape knowledgebase to relate genetic perturbations to phenotypic evolution P Manda, JP Balhoff, H Lapp, P Mabee, TJ Vision genesis 53 (8), 561-571, 2015 | 20 | 2015 |
| Annotation of phenotypes using ontologies: a gold standard for the training and evaluation of natural language processing systems W Dahdul, P Manda, H Cui, JP Balhoff, TA Dececchi, N Ibrahim, H Lapp, ... Database 2018, 2018 | 19 | 2018 |
| GOModeler- A tool for hypothesis-testing of functional genomics datasets P Manda, MKG Freeman, SM Bridges, TJ Jankun-Kelly, B Nanduri, ... BMC bioinformatics 11, 1-12, 2010 | 17 | 2010 |
| Machine learning for predicting readmission risk among the frail: Explainable AI for healthcare SD Mohanty, D Lekan, TP McCoy, M Jenkins, P Manda Patterns 3 (1), 100395, 2022 | 13 | 2022 |
| What’s hot and what’s not? - exploring trends in bioinformatics literature using topic modeling and keyword analysis A Hahn, SD Mohanty, P Manda International Symposium on Bioinformatics Research, 2017, 2017 | 11 | 2017 |
| Comparison of natural language processing tools for automatic gene ontology annotation of scientific literature L Beasley, P Manda PeerJ Preprints, 2018 | 10 | 2018 |
| Taking a dive: Experiments in deep learning for automatic ontology-based annotation of scientific literature P Manda, L Beasley, SD Mohanty bioRxiv, 365874, 2018 | 9 | 2018 |
| Automated ontology-based annotation of scientific literature using deep learning P Manda, S SayedAhmed, SD Mohanty Proceedings of The International Workshop on Semantic Big Data, 1-6, 2020 | 8 | 2020 |
| Data mining powered by the gene ontology P Manda Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 10 (3 …, 2020 | 8 | 2020 |
| Comparison of a frailty risk score and comorbidity indices for hospital readmission using electronic health record data DA Lekan, TP McCoy, M Jenkins, S Mohanty, P Manda, R Yasin Research in Gerontological Nursing 14 (2), 91-103, 2021 | 7 | 2021 |
| Phenoscape: Semantic analysis of organismal traits and genes yields insights in evolutionary biology PM Mabee, WM Dahdul, JP Balhoff, H Lapp, P Manda, JC Uyeda, ... PeerJ, 2018 | 6 | 2018 |
| A multi-modal machine learning approach towards predicting patient readmission SD Mohanty, D Lekan, TP McCoy, M Jenkins, P Manda 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2020 | 4 | 2020 |
| Using Manual and Computer-Based Text-Mining to Uncover Research Trends for Apis mellifera E Amiri, P Waiker, O Rueppell, P Manda Veterinary Sciences 7 (2), 61, 2020 | 4 | 2020 |
| Measuring the importance of annotation granularity to the detection of semantic similarity between phenotype profiles P Manda, JP Balhoff, TJ Vision bioRxiv, 086306, 2016 | 4 | 2016 |
| Investigating the importance of anatomical homology for cross-species phenotype comparisons using semantic similarity. P Manda, CJ Mungall, JP Balhoff, H Lapp, TJ Vision Pacific Symposium on Biocomputing, 2016 | 4 | 2016 |
