Sudip Sharma
Temple University
10 Papers
49 Citations
Sudip Sharma is an academic researcher from Temple University. The author has contributed to research in topics: Computer science & Phylogenomics. The author has an hindex of 2, co-authored 7 publications.
Chat about Author
Papers
An evolutionary portrait of the progenitor SARS-CoV-2 and its dominant offshoots in COVID-19 pandemic.
Sudhir Kumar,Sudhir Kumar,Qiqing Tao,Steven Weaver,Maxwell Sanderford,Marcos A. Caraballo-Ortiz,Sudip Sharma,Sergei L Kosakovsky Pond,Sayaka Miura +8 more
TL;DR: The most recent common ancestor of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was reconstructed through a novel application and advancement of computational methods initially developed to infer the mutational history of tumor cells in a patient as discussed by the authors.
78
An evolutionary portrait of the progenitor SARS-CoV-2 and its dominant offshoots in COVID-19 pandemic
Sudhir Kumar,Qiqing Tao,Steven Weaver,Maxwell Sanderford,Marcos A. Caraballo-Ortiz,Sudip Sharma,Sergei L Kosakovsky Pond,Sayaka Miura +7 more
TL;DR: Fingerprinting based on common mutations reveals that the same coronavirus lineage has dominated North America for most of the pandemic and provides a continually updating dashboard of global evolution and spatiotemporal trends of SARS-CoV-2 spread.
Fast and accurate bootstrap confidence limits on genome-scale phylogenies using little bootstraps.
Sudip Sharma,Sudhir Kumar,Sudhir Kumar +2 more
- 01 Sep 2021
TL;DR: The median bagging of bootstrap confidence limits from little samples produces confidence in inferred species relationships similar to standard bootstrap but in a fraction of computational time and memory, which can potentially enhance the rigor, efficiency, and parallelization of big data phylogenomic analyses.
15
Evolutionary Sparse Learning for Phylogenomics.
TL;DR: ESL as mentioned in this paper is a supervised machine learning approach with sparsity constraints for phylogenomics, referred to as evolutionary sparse learning (ESL). ESL builds models with genomic loci (e.g., genes, proteins, genomic segments, and positions) as parameters.
10
CDK4 as a phytochemical based anticancer drug target
R. K. Chando,Nazmul Hussain,M. Islam Rana,S. Sayed,Sadab Alam,T. Ahmed Fakir,Sudip Sharma,A. Rahman Tanu,A. Rahman Tanu,F. Mobin,E. Hoque Apu,Md. Kamrul Hasan,Md. Abu Sayed,Mohammad Arif Ashraf +13 more
TL;DR: It is demonstrated that simple mango tree extracted active compounds, mangiferin, can work as potential anticancer drug and leveraging the recent advancement of sequencing and gene expression data can accelerate the phytochemical based drug discovery process.