Author

Rakshanda Sajeed

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· 1 Genetics· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:differential expression· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Assay:protein sequence· 1 Research Focus:protein structure prediction· 1 Research Focus:variant effect prediction· 1 Assay:whole-exome sequencing· 1

Frequent Co-Authors

Rajgopal Srinivasan· 2 shared Sadhna RanaiD· 2 shared Swatantra Pradhan· 2 shared Ailin Glagovsky· 1 shared Akash Kamandula· 1 shared Amanda M. WilliamsiD· 1 shared Andrea GrafmülleriD· 1 shared Andrzej KloczkowskiiD· 1 shared

Activity by Year

2025-2025 · peak 2/yr

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10 top collaborators · 45 mutual co-author links

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2 shared papersBioinformatics

Rajgopal Srinivasan

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintJul 29, 2025

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.

DOI 10.1101/2025.07.29.667398

protein sequencedeep learning

𝕏 PostBluesky

GeneticsHuman GeneticsPeer-reviewedMar 1, 2025

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

Shantanu Jain, Marena I. Trinidad, Thanh Nguyen…·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.

4 citations

humanwhole-exome sequencing

𝕏 PostBluesky