A practical guide to methods controlling false discoveries in computational biology K Korthauer, PK Kimes, C Duvallet, A Reyes, A Subramanian, M Teng, ... Genome biology 20, 1-21, 2019 | 270 | 2019 |
A machine learning approach enables quantitative measurement of liver histology and disease monitoring in NASH A Taylor‐Weiner, H Pokkalla, L Han, C Jia, R Huss, C Chung, H Elliott, ... Hepatology 74 (1), 133-147, 2021 | 132 | 2021 |
High‐throughput identification of RNA nuclear enrichment sequences CJ Shukla, AL McCorkindale, C Gerhardinger, KD Korthauer, MN Cabili, ... The EMBO journal 37 (6), e98452, 2018 | 109 | 2018 |
Function and evolution of local repeats in the Firre locus E Hacisuleyman, CJ Shukla, CL Weiner, JL Rinn Nature communications 7 (1), 11021, 2016 | 84 | 2016 |
A gene expression atlas of embryonic neurogenesis in Drosophila reveals complex spatiotemporal regulation of lncRNAs AL McCorkindale, P Wahle, S Werner, I Jungreis, P Menzel, CJ Shukla, ... Development 146 (6), dev175265, 2019 | 24 | 2019 |
Assessing fashion recommendations: A multifaceted offline evaluation approach J Sherman, C Shukla, R Textor, S Zhang, AA Winecoff arXiv preprint arXiv:1909.04496, 2019 | 4 | 2019 |
Validation of a machine learning-based approach (DELTA liver fibrosis score) for the assessment of histologic response in patients with advanced fibrosis due to NASH AH Taylor-Weiner, H Pokkalla, L Han, C Jia, R Huss, C Chung, H Elliott, ... The Liver Meeting Digital Experience™, 2020 | 2 | 2020 |
MACHINE LEARNING ENABLES QUANTITATIVE ASSESSMENT OF HISTOPATHOLOGIC SIGNATURES ASSOCIATED WITH ALT NORMALIZATION IN CHRONIC HEPATITIS B PATIENTS TREATED WITH TENOFOVIR … C Shukla, O Carrasco-Zevallos, D Juyal, NHQ Le, V Mountain, H Pokkalla, ... The Liver Meeting Digital Experience™, 2020 | | 2020 |
A MACHINE LEARNING MODEL BASED ON LIVER HISTOLOGY PREDICTS THE HEPATIC VENOUS PRESSURE GRADIENT (HVPG) IN PATIENTS WITH COMPENSATED CIRRHOSIS DUE TO NONALCOHOLIC … J Bosch, SA Harrison, MF Abdelmalek, ML Shiffman, DC Rockey, D Juyal, ... The Liver Meeting Digital Experience™, 2020 | | 2020 |
MACHINE LEARNING BASED QUANTIFICATION OF HISTOLOGY FEATURES FROM PATIENTS TREATED FOR CHRONIC HEPATITIS B IDENTIFIES FEATURES ASSOCIATED WITH VIRAL DNA SUPPRESSION AND HBEAG LOSS C Shukla, O Carrasco-Zevallos, D Juyal, NHQ Le, V Mountain, H Pokkalla, ... The Liver Meeting Digital Experience™, 2020 | | 2020 |
Machine learning identifies histologic features associated with regression of cirrhosis in treatment for chronic hepatitis B D Juyal, C Shukla, H Pokkalla, A Taylor, O Zevallos, M Resnick, ... Journal of Hepatology 73, S140-S141, 2020 | | 2020 |
Identifying and Characterizing Functional Sequence Elements in Long Noncoding RNAs C Shukla | | 2018 |
A Machine Learning Approach Enables Quantitative Measurement of Liver Histology and Disease Monitoring in NASH H Pokkalla, C Chung, I Elliott, B Hunter Glass, K Pethia, ... | | |