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ORCIDYasha Hasija
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2020 – today
- 2024
[j12]Nakul Tanwar, Yasha Hasija
:
Explicate molecular landscape of combined pulmonary fibrosis and emphysema through explainable artificial intelligence: a comprehensive analysis of ILD and COPD interactions using RNA from whole lung homogenates. Medical Biol. Eng. Comput. 62(8): 2557-2570 (2024)- 2023
- [j11]Rajkumar Chakraborty, Yasha Hasija:
Utilizing deep learning to explore chemical space for drug lead optimization. Expert Syst. Appl. 229(Part A): 120592 (2023) - [c5]Shreya Bhardwaj, Yasha Hasija:
ChatGPT, a powerful language model and its potential uses in bioinformatics. ICCCNT 2023: 1-6 - 2022
- [j10]Jaishree Meena, Yasha Hasija:
Application of explainable artificial intelligence in the identification of Squamous Cell Carcinoma biomarkers. Comput. Biol. Medicine 146: 105505 (2022) - [j9]Rajkumar Chakraborty, Gourab Bhattacharje, Joydeep Baral, Bharat Manna, Jayati Mullick, Basavaraj S. Mathapati, Priya Abraham, Madhumathi J, Yasha Hasija, Amit Ghosh, Amit Kumar Das:
In-silico screening and in-vitro assay show the antiviral effect of Indomethacin against SARS-CoV-2. Comput. Biol. Medicine 147: 105788 (2022) - [j8]Rajkumar Chakraborty, Yasha Hasija:
Predicting protein intrinsically disordered regions by applying natural language processing practices. Soft Comput. 26(22): 12343-12353 (2022) - [i1]Divyanshu Aggarwal, Yasha Hasija:
A Review of Deep Learning Techniques for Protein Function Prediction. CoRR abs/2211.09705 (2022) - 2021
- [c4]Prodyot Banerjee, Yasha Hasija:
Molecular Dynamics Simulation and Its Application. ICCCNT 2021: 1-5 - [c3]Aparna Chauhan, Kuldeep Singh Naga, Yasha Hasija:
Pharmacogenomics Based Study for Liraglutide And Metfromin (PCOS Drugs) Efficacy In Populations Across The Globe. ICCCNT 2021: 1-6 - [c2]Divya Sharma, Yasha Hasija:
Big Data: A Boom in biomedical sciences. ICCCNT 2021: 1-5 - 2020
- [j7]Rajkumar Chakraborty, Yasha Hasija:
Predicting MicroRNA Sequence Using CNN and LSTM Stacked in Seq2Seq Architecture. IEEE ACM Trans. Comput. Biol. Bioinform. 17(6): 2183-2188 (2020)
2010 – 2019
- 2019
- [j6]Kirti Bhadhadhara, Yasha Hasija:
ARD-PRED: an in silico tool for predicting age-related-disorder-associated proteins. Soft Comput. 23(5): 1767-1776 (2019) - 2018
- [j5]Rajkumar Chakraborty, Himani Gupta, Razia Rahman, Yasha Hasija:
In silico analysis of nsSNPs in ABCB1 gene affecting breast cancer associated protein P-glycoprotein (P-gp). Comput. Biol. Chem. 77: 430-441 (2018) - 2017
- [j4]Abhivyakti Srivastava, Mottadi Shiva, Priyanka Kumari, Yasha Hasija:
Extensive computational analysis of chromosome 11. Int. J. Bioinform. Res. Appl. 13(3): 242-263 (2017) - [c1]Priyanka Kumari, Arpit Singh, Yasha Hasija:
Functional Annotation of Hypothetical proteins of Lactobacillus rhamnosus: An In Silico Approach. ICBBS 2017: 65-69 - 2016
- [j3]Isha Srivastava, Lokesh Kumar Gahlot, Pooja Khurana, Yasha Hasija:
dbAARD & AGP: A computational pipeline for the prediction of genes associated with age related disorders. J. Biomed. Informatics 60: 153-161 (2016) - 2014
- [j2]Ruchika Sahajpal, Gaurav Kandoi, Heena Dhiman, Sweety Raj, Vinod Scaria, Deeksha Bhartiya, Yasha Hasija:
HGV&TB: a comprehensive online resource on human genes and genetic variants associated with tuberculosis. Database J. Biol. Databases Curation 2014 (2014) - [j1]Deepika Jaggi, Heena Dhiman, Sonam Arora, Vidhi Malik, Yasha Hasija:
Personal genome analysis: a tread towards personalised medicine. Int. J. Funct. Informatics Pers. Medicine 4(3/4): 198-225 (2014)
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