Author

V P Brintha

Indian Institute of Technology Madras

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· 3 Genomics· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Approach:statistical model· 3 Research Focus:benchmarking· 2 Research Focus:differential expression· 2 Assay:whole-genome sequencing· 2 Approach:benchmark study· 1 Assay:bulk RNA-seq· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

Manikandan NarayananiD· 4 shared Amol Dumrewal· 1 shared Ansh Meshram· 1 shared Deepti PVS· 1 shared Rahul Biswas· 1 shared S Ashok Kumar· 1 shared Saish JaiswaliD· 1 shared Sidharthan S C· 1 shared

Activity by Year

2023-2026 · peak 2/yr

Co-Author Collaboration Network

9 top collaborators · 16 mutual co-author links

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4 shared papersBioinformatics

Manikandan NarayananORCID

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4 papers

Recent·Most cited

TB-Bench: A Systematic Benchmark of Machine Learning and Deep Learning Methods for Second-Line TB Drug Resistance Prediction

V P Brintha, Saish Jaiswal, Ansh Meshram, Deepti PVS, Sidharthan S C, Manikandan Narayanan

TB-Bench benchmarks ML and DL models for predicting second-line TB drug resistance using WGS data, finding traditional ML models outperform DL models in internal testing but show comparable performance in external validation.

bioRxiv · Apr 13, 2026 · PreprintBioinformatics

Dissecting the effect of single- and co- infection of TB and COVID-19 pathogens on the sputum microbiome

V P Brintha, S Ashok Kumar, Sivakumar Shanmugam, Manikandan Narayanan

This study investigates how TB and COVID-19 co-infection affects the sputum microbiome, finding altered bacterial abundance and functional pathways that may impact treatment outcomes.

bioRxiv · Jul 8, 2025 · PreprintGenomics

Demixer: A probabilistic generative model to delineate different strains of a microbial species in a mixed infection sample

V P Brintha, Manikandan Narayanan

Demixer identifies strain proportions and identities in mixed infection samples using a probabilistic generative model, achieving high accuracy in both synthetic and real-world datasets.

Bioinformatics · Mar 29, 2025Peer-reviewedBioinformatics

Robust discovery of causal gene networks via measurement error estimation and correction

Rahul Biswas, V P Brintha, Amol Dumrewal, Manikandan Narayanan

This study introduces RCD, a method to improve causal gene network discovery by correcting measurement errors, showing better performance on simulated and yeast data and identifying causal relations in human skeletal muscle.

bioRxiv · May 9, 2023 · PreprintBioinformatics