Debasis Dash
Scientist-G |
Decision Unit 4: Systems Biology
Professor |
Academy of Scientific and Innovative Research
Debasis Dash is interested in developing algorithms and tools in the area of computational biology.
Specific Interests
- Proteome informatics using mass spectrometry
- Analysis of exomes and metagenomes
- Understanding molecular variations and their systemic impact through Ayurgenomics
His group has developed several tools and algorithms such as GenoCluster for protein-coding gene identification, PLHost for protein function assignment, and machine learning tools like "Pro-Gyan" for protein classification. Other tools include MassWiz, Genosuite, and Proteostat for proteomics. Through collaborations, his work also focuses on Ayurgenomics and deciphering molecular signatures of extra-pulmonary tuberculosis.
Selected Publications
All Citations →- Whole-Exome Sequencing of Vitiligo Lesions Indicates Lower Burden of Somatic Variations: Implications in Risk for Nonmelanoma Skin Cancers. Gupta I, Shankrit S, Narta K, Ghazi M, Grover R, Pandey R, Kar HK, Menon SM, Gupta A, Yenamandra VK, Singh A, Mukerji M, Mukhopadhyay A, Rani R, Gokhale RS, Dash D, Natarajan VT. J Invest Dermatol. 2023 Jun;143(6):1111-1114.e8.
- A machine learning-based approach to determine infection status in recipients of BBV152 (Covaxin) whole-virion inactivated SARS-CoV-2 vaccine for serological surveys. Singh P, Ujjainiya R, Prakash S, Naushin S, Sardana V, [...] Agrawal A, Sengupta S, Dash D. Comput Biol Med. 2022 Jul;146:105419.
- High failure rate of ChAdOx1-nCoV19 immunization during Delta surge. Nat Commun (2022).
- Validation of expert system enhanced deep learning algorithm for automated screening for COVID-Pneumonia on chest X-rays. Gidde PS, Prasad SS, Singh AP, Bhatheja N, Prakash S, Singh P, Saboo A, Takhar R, Gupta S, Saurav S, M V R, Singh A, Sardana V, Mahajan H, Kalyanpur A, Mandal AS, Mahajan V, Agrawal A, Agrawal A, Venugopal VK, Singh S, Dash D. Sci Rep. 2021 Dec 1;11(1):23210.
- VitiVar: A locus specific database of vitiligo associated genes and variations. Gupta I, Narang A, Singh P, Manchanda V, Khanna S; Indian Genome Variation Consortium; Mukerji M, Natarajan VT, Dash D. Gene X. 2019 May 11;3:100018.