Author

Swatantra Pradhan

Tata Consultancy Services (India)

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 2 Genetics· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Organism:human· 2 Approach:machine learning (classical)· 2 Research Focus:benchmarking· 1 Research Focus:differential expression· 1 Assay:multiome· 1 Assay:protein sequence· 1 Research Focus:protein structure prediction· 1

Frequent Co-Authors

Rajgopal Srinivasan· 3 shared Sadhna RanaiD· 3 shared Rakshanda Sajeed· 2 shared Aakansha RaiiD· 1 shared Ádám Misák· 1 shared Ailin Glagovsky· 1 shared Akash Gosain· 1 shared Akash Kamandula· 1 shared

Activity by Year

2021-2025 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 30 mutual co-author links

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3 shared papersBioinformatics

Rajgopal Srinivasan

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3 papers

Recent·Most cited

An improved deep learning model for immunogenic B epitope prediction

Rakshanda Sajeed, Swatantra Pradhan, Rajgopal Srinivasan, Sadhna Rana

This study improves B epitope prediction by combining protein embeddings with structural features, showing better performance than models using embeddings alone.

bioRxiv · Jul 29, 2025 · PreprintBioinformatics

Evaluation of enzyme activity predictions for variants of unknown significance in Arylsulfatase A

Shantanu Jain, Marena I. Trinidad, Thanh Nguyen, Kaiya Jones, Santiago Diaz Neto, Fang Ge, Ailin Glagovsky, Cameron Jones, Giankaleb Moran, Boqi Wang, Kobra Rahimi, Sümeyra Zeynep Çalıcı, Luis R. Cedillo, Silvia Berardelli, Buse Özden, , Wyatt Travis Clark

The paper evaluates variant effect predictions for ARSA gene variants, finding that a bootcamp-trained model outperformed others and that deep learning slightly improved performance over simpler methods.

Human Genetics · Mar 1, 2025Peer-reviewedGenetics

Cell-to-cell and type-to-type heterogeneity of signaling networks: Insights from the crowd

Attila Gábor, Marco Tognetti, Alice Driessen, Jovan Tanevski, Baosen Guo, Wencai Cao, He Shen, Thomas Von Yu, Verena Chung, Bernd Bodenmiller, Julio Sáez-Rodríguez, Augustinas Prusokas, Alidivinas Prusokas, Renata Retkutė, Anand Rajasekar, , Mingyu Lee

The paper organizes a DREAM challenge to benchmark predictive models of single-cell signaling using mass cytometry data from breast cancer cell lines.

Molecular Systems Biology · Oct 1, 2021Peer-reviewedBioinformatics