An expanded evaluation of protein function prediction methods shows an improvement in accuracy Y Jiang, TR Oron, WT Clark, AR Bankapur, D D’Andrea, R Lepore, ... Genome biology 17, 1-19, 2016 | 417 | 2016 |
Deep learning-based advances in protein structure prediction SC Pakhrin, B Shrestha, B Adhikari, DB Kc International journal of molecular sciences 22 (11), 5553, 2021 | 82 | 2021 |
Comparison of machine learning and deep learning models for network intrusion detection systems N Thapa, Z Liu, DB Kc, B Gokaraju, K Roy Future Internet 12 (10), 167, 2020 | 69 | 2020 |
RF‐Phos: A novel general phosphorylation site prediction tool based on random Forest HD Ismail, A Jones, JH Kim, RH Newman, DB Kc BioMed research international 2016 (1), 3281590, 2016 | 58 | 2016 |
DeepSuccinylSite: a deep learning based approach for protein succinylation site prediction N Thapa, M Chaudhari, S McManus, K Roy, RH Newman, H Saigo, DB Kc BMC bioinformatics 21, 1-10, 2020 | 53 | 2020 |
Recent advances in sequence-based protein structure prediction DB Kc Briefings in bioinformatics 18 (6), 1021-1032, 2017 | 50 | 2017 |
Protein side-chain packing problem: a maximum edge-weight clique algorithmic approach KC Dukka Bahadur, E Tomita, J Suzuki, T Akutsu Journal of bioinformatics and computational biology 3 (01), 103-126, 2005 | 47 | 2005 |
Point matching under non-uniform distortions and protein side chain packing based on an efficient maximum clique algorithm DB KC, T Akutsu, E Tomita, T Seki, A Fujiyama Genome Informatics 13, 143-152, 2002 | 40 | 2002 |
Structure-based methods for computational protein functional site prediction BKC Dukka Computational and structural biotechnology journal 8 (11), e201308005, 2013 | 38 | 2013 |
RF-GlutarySite: a random forest based predictor for glutarylation sites HJ Al-Barakati, H Saigo, RH Newman, DB KC Molecular omics 15 (3), 189-204, 2019 | 37 | 2019 |
Numerical and experimental investigation of hydrodynamics and light transfer in open raceway ponds at various algal cell concentrations and medium depths H Amini, A Hashemisohi, L Wang, A Shahbazi, M Bikdash, KC Dukka, ... Chemical Engineering Science 156, 11-23, 2016 | 35 | 2016 |
CNN-BLPred: a convolutional neural network based predictor for β-lactamases (BL) and their classes C White, HD Ismail, H Saigo, DB Kc BMC bioinformatics 18, 221-232, 2017 | 30 | 2017 |
RF-Hydroxysite: a random forest based predictor for hydroxylation sites HD Ismail, RH Newman, D B KC Molecular BioSystems 12 (8), 2427-2435, 2016 | 28 | 2016 |
Improving protein succinylation sites prediction using embeddings from protein language model S Pokharel, P Pratyush, M Heinzinger, RH Newman, DB Kc Scientific reports 12 (1), 16933, 2022 | 26 | 2022 |
DeepRMethylSite: a deep learning based approach for prediction of arginine methylation sites in proteins M Chaudhari, N Thapa, K Roy, RH Newman, H Saigo, KC Dukka B Molecular omics 16 (5), 448-454, 2020 | 24 | 2020 |
Multiple methods for protein side chain packing using maximum weight cliques B JB, DB KC, E Tomita, T Akutsu Genome Informatics 17 (1), 3-12, 2006 | 22 | 2006 |
The PFP and ESG protein function prediction methods in 2014: effect of database updates and ensemble approaches IK Khan, Q Wei, S Chapman, DB Kc, D Kihara GigaScience 4 (1), s13742-015-0083-4, 2015 | 21 | 2015 |
SymD webserver: a platform for detecting internally symmetric protein structures CH Tai, R Paul, D Kc, JD Shilling, B Lee Nucleic Acids Research 42 (W1), W296-W300, 2014 | 21 | 2014 |
Improving position-specific predictions of protein functional sites using phylogenetic motifs KC Dukka Bahadur, DR Livesay Bioinformatics 24 (20), 2308-2316, 2008 | 20 | 2008 |
An integrated growth kinetics and computational fluid dynamics model for the analysis of algal productivity in open raceway ponds H Amini, L Wang, A Hashemisohi, A Shahbazi, M Bikdash, KC Dukka, ... Computers and Electronics in Agriculture 145, 363-372, 2018 | 19 | 2018 |