| High-depth African genomes inform human migration and health A Choudhury, S Aron, LR Botigué, D Sengupta, G Botha, T Bensellak, ... Nature 586 (7831), 741-748, 2020 | 313 | 2020 |
| Computational/in silico methods in drug target and lead prediction FE Agamah, GK Mazandu, R Hassan, CD Bope, NE Thomford, ... Briefings in bioinformatics 21 (5), 1663-1675, 2020 | 242 | 2020 |
| Energy constrained multipath routing in wireless sensor networks AB Bagula, GK Mazandu International Conference on Ubiquitous Intelligence and Computing, 453-467, 2008 | 140 | 2008 |
| Function Prediction and Analysis of Mycobacterium tuberculosis Hypothetical Proteins GK Mazandu, NJ Mulder International journal of molecular sciences 13 (6), 7283-7302, 2012 | 122 | 2012 |
| Gene ontology semantic similarity tools: survey on features and challenges for biological knowledge discovery GK Mazandu, ER Chimusa, NJ Mulder Briefings in bioinformatics 18 (5), 886-901, 2017 | 105 | 2017 |
| A topology‐based metric for measuring term similarity in the gene ontology GK Mazandu, NJ Mulder Advances in bioinformatics 2012 (1), 975783, 2012 | 78 | 2012 |
| Information Content‐Based Gene Ontology Semantic Similarity Approaches: Toward a Unified Framework Theory GK Mazandu, NJ Mulder BioMed research international 2013 (1), 292063, 2013 | 75 | 2013 |
| Information content-based gene ontology functional similarity measures: which one to use for a given biological data type? GK Mazandu, NJ Mulder PloS one 9 (12), e113859, 2014 | 57 | 2014 |
| Using biological networks to improve our understanding of infectious diseases NJ Mulder, RO Akinola, GK Mazandu, H Rapanoel Computational and structural biotechnology journal 11 (18), 1-10, 2014 | 56 | 2014 |
| A comprehensive survey of models for dissecting local ancestry deconvolution in human genome E Geza, J Mugo, NJ Mulder, A Wonkam, ER Chimusa, GK Mazandu Briefings in bioinformatics 20 (5), 1709-1724, 2019 | 49 | 2019 |
| DaGO-Fun: tool for Gene Ontology-based functional analysis using term information content measures GK Mazandu, NJ Mulder BMC bioinformatics 14, 1-13, 2013 | 48 | 2013 |
| Generation and Analysis of Large‐Scale Data‐Driven Mycobacterium tuberculosis Functional Networks for Drug Target Identification GK Mazandu, NJ Mulder Advances in Bioinformatics 2011 (1), 801478, 2011 | 47 | 2011 |
| Computational approaches for network-based integrative multi-omics analysis FE Agamah, JR Bayjanov, A Niehues, KF Njoku, M Skelton, GK Mazandu, ... Frontiers in Molecular Biosciences 9, 967205, 2022 | 44 | 2022 |
| Predicting and Analyzing Interactions between Mycobacterium tuberculosis and Its Human Host HA Rapanoel, GK Mazandu, NJ Mulder PloS one 8 (7), e67472, 2013 | 44 | 2013 |
| Implementing artificial intelligence and digital health in resource-limited settings? Top 10 lessons we learned in congenital heart defects and cardiology NE Thomford, CD Bope, FE Agamah, K Dzobo, R Owusu Ateko, ... Omics: a journal of integrative biology 24 (5), 264-277, 2020 | 37 | 2020 |
| SickleInAfrica J Makani, RZ Sangeda, O Nnodu, V Nembaware, A Osei-Akoto, V Paintsil, ... The Lancet Haematology 7 (2), e98-e99, 2020 | 36 | 2020 |
| ancGWAS: a post genome-wide association study method for interaction, pathway and ancestry analysis in homogeneous and admixed populations ER Chimusa, M Mbiyavanga, GK Mazandu, NJ Mulder Bioinformatics 32 (4), 549-556, 2016 | 35 | 2016 |
| A-DaGO-Fun: an adaptable Gene Ontology semantic similarity-based functional analysis tool GK Mazandu, ER Chimusa, M Mbiyavanga, NJ Mulder Bioinformatics 32 (3), 477-479, 2016 | 35 | 2016 |
| Scoring protein relationships in functional interaction networks predicted from sequence data GK Mazandu, NJ Mulder PLoS One 6 (4), e18607, 2011 | 35 | 2011 |
| A web-based protein interaction network visualizer GA Salazar, A Meintjes, GK Mazandu, HA Rapanoël, RO Akinola, ... BMC bioinformatics 15, 1-8, 2014 | 34 | 2014 |
Prof Ambroise Wonkam, MD, DMedSc,...Division of Human Genetics - Faculty of Health Sciences - University of Cape Town - South AfricaVerified email at uct.ac.za
