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Avi Srivastava
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2020 – today
- 2022
- [j10]Wancen Mu, Hirak Sarkar
, Avi Srivastava
Airpart: interpretable statistical models for analyzing allelic imbalance in single-cell datasets. Bioinform. 38(10): 2773-2780 (2022) - 2021
- [j9]Scott Van Buren, Hirak Sarkar
Compression of quantification uncertainty for scRNA-seq counts. Bioinform. 37(12): 1699-1707 (2021) - [j8]Charlotte Soneson
Preprocessing choices affect RNA velocity results for droplet scRNA-seq data. PLoS Comput. Biol. 17(1) (2021) - 2020
- [j7]Hirak Sarkar
Terminus enables the discovery of data-driven, robust transcript groups from RNA-seq data. Bioinform. 36(Supplement-1): i102-i110 (2020) - [j6]Avi Srivastava, Laraib Malik, Hirak Sarkar
A Bayesian framework for inter-cellular information sharing improves dscRNA-seq quantification. Bioinform. 36(Supplement-1): i292-i299 (2020)
2010 – 2019
- 2019
- [j5]Hirak Sarkar
Minnow: a principled framework for rapid simulation of dscRNA-seq data at the read level. Bioinform. 35(14): i136-i144 (2019) - 2018
- [j4]Fatemeh Almodaresi, Hirak Sarkar
A space and time-efficient index for the compacted colored de Bruijn graph. Bioinform. 34(13): i169-i177 (2018) - [c1]Sheetal Pandrekar Mangesh, Xin Chen, Gaurav Gopalkrishna, Avi Srivastava, Mary M. Saltz, Joel H. Saltz, Fusheng Wang:
Social Media Based Analysis of Opioid Epidemic Using Reddit. AMIA 2018 - 2017
- [j3]Mohsen Zakeri, Avi Srivastava
Improved data-driven likelihood factorizations for transcript abundance estimation. Bioinform. 33(14): i142-i151 (2017) - 2016
- [j2]Avi Srivastava
RapMap: a rapid, sensitive and accurate tool for mapping RNA-seq reads to transcriptomes. Bioinform. 32(12): 192-200 (2016) - [i1]Avi Srivastava, Hirak Sarkar
Accurate, Fast and Lightweight Clustering of de novo Transcriptomes using Fragment Equivalence Classes. CoRR abs/1604.03250 (2016) - 2014
- [j1]Kuldeep Yadav, Avi Srivastava
Texture-based medical image retrieval in compressed domain using compressive sensing. Int. J. Bioinform. Res. Appl. 10(2): 129-144 (2014)
Coauthor Index
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