| Methods of integrating data to uncover genotype–phenotype interactions MD Ritchie, ER Holzinger, R Li, SA Pendergrass, D Kim Nature Reviews Genetics 16 (2), 85-97, 2015 | 1061 | 2015 |
| Predicting Alzheimer’s disease progression using multi-modal deep learning approach G Lee, K Nho, B Kang, KA Sohn, D Kim Scientific reports 9 (1), 1952, 2019 | 389 | 2019 |
| Robust predictive model for evaluating breast cancer survivability K Park, A Ali, D Kim, Y An, M Kim, H Shin Engineering Applications of Artificial Intelligence 26 (9), 2194-2205, 2013 | 189 | 2013 |
| Synergistic effect of different levels of genomic data for cancer clinical outcome prediction D Kim, H Shin, YS Song, JH Kim Journal of biomedical informatics 45 (6), 1191-1198, 2012 | 114 | 2012 |
| Knowledge boosting: a graph-based integration approach with multi-omics data and genomic knowledge for cancer clinical outcome prediction D Kim, JG Joung, KA Sohn, H Shin, YR Park, MD Ritchie, JH Kim Journal of the American Medical Informatics Association 22 (1), 109-120, 2015 | 112 | 2015 |
| ATHENA: Identifying interactions between different levels of genomic data associated with cancer clinical outcomes using grammatical evolution neural network D Kim, R Li, SM Dudek, MD Ritchie BioData mining 6, 1-14, 2013 | 85 | 2013 |
| Identification of epigenetic interactions between miRNA and DNA methylation associated with gene expression as potential prognostic markers in bladder cancer M Shivakumar, Y Lee, L Bang, T Garg, KA Sohn, D Kim BMC medical genomics 10, 65-75, 2017 | 63 | 2017 |
| Human-Disease Phenotype Map Derived from PheWAS across 38,682 Individuals A Verma, L Bang, JE Miller, Y Zhang, MTM Lee, Y Zhang, ... The American Journal of Human Genetics, 2019 | 55 | 2019 |
| Min-redundancy and max-relevance multi-view feature selection for predicting ovarian cancer survival using multi-omics data Y EL-Manzalawy, TY Hsieh, M Shivakumar, D Kim, V Honavar BMC Medical Genomics 11 (Suppl 3), 71, 2018 | 54 | 2018 |
| MildInt: deep learning-based multimodal longitudinal data integration framework G Lee, B Kang, K Nho, KA Sohn, D Kim Frontiers in genetics 10, 617, 2019 | 49 | 2019 |
| Using knowledge-driven genomic interactions for multi-omics data analysis: metadimensional models for predicting clinical outcomes in ovarian carcinoma D Kim, R Li, A Lucas, SS Verma, SM Dudek, MD Ritchie Journal of the American Medical Informatics Association 24 (3), 577-587, 2017 | 48 | 2017 |
| The joint effect of air pollution exposure and copy number variation on risk for autism D Kim, H Volk, S Girirajan, S Pendergrass, MA Hall, SS Verma, ... Autism Research 10 (9), 1470-1480, 2017 | 47 | 2017 |
| Predicting censored survival data based on the interactions between meta-dimensional omics data in breast cancer D Kim, R Li, SM Dudek, MD Ritchie Journal of biomedical informatics 56, 220-228, 2015 | 42 | 2015 |
| Association analysis of rare variants near the APOE region with CSF and neuroimaging biomarkers of Alzheimer’s disease K Nho, S Kim, E Horgusluoglu, SL Risacher, L Shen, D Kim, S Lee, ... BMC medical genomics 10, 45-52, 2017 | 36 | 2017 |
| Incorporating inter-relationships between different levels of genomic data into cancer clinical outcome prediction D Kim, H Shin, KA Sohn, A Verma, MD Ritchie, JH Kim Methods 67 (3), 344-353, 2014 | 36 | 2014 |
| Preparing next-generation scientists for biomedical big data: artificial intelligence approaches JH Moore, MR Boland, PG Camara, H Chervitz, G Gonzalez, BE Himes, ... Personalized medicine 16 (3), 247-257, 2019 | 35 | 2019 |
| Integration of bioinformatics and imaging informatics for identifying rare PSEN1 variants in Alzheimer’s disease K Nho, E Horgusluoglu, S Kim, SL Risacher, D Kim, T Foroud, PS Aisen, ... BMC medical genomics 9, 11-18, 2016 | 34 | 2016 |
| PLATO software provides analytic framework for investigating complexity beyond genome-wide association studies MA Hall, J Wallace, A Lucas, D Kim, AO Basile, SS Verma, CA McCarty, ... Nature Communications 8 (1), 1167, 2017 | 33 | 2017 |
| Ideas for how informaticians can get involved with COVID-19 research JH Moore, I Barnett, MR Boland, Y Chen, G Demiris, ... BioData mining 13, 1-16, 2020 | 32 | 2020 |
| Population-dependent intron retention and DNA methylation in breast cancer D Kim, M Shivakumar, S Han, MS Sinclair, YJ Lee, Y Zheng, OI Olopade, ... Molecular Cancer Research 16 (3), 461-469, 2018 | 30 | 2018 |
Marylyn D RitchieUniversity of PennsylvaniaVerified email at upenn.edu
