Author

Mahima Yadav

Institute of Medical SciencesORCID 0000-0002-2282-2385Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:differential expression· 3 Approach:machine learning (classical)· 3 Assay:bulk RNA-seq· 2 Organism:human· 2 Research Focus:benchmarking· 1 Research Focus:database / resource· 1 Research Focus:software / tool· 1 Approach:statistical model· 1

Frequent Co-Authors

Abhay Kumar PathakiD· 3 shared Garima JainiD· 3 shared Lalit KumariD· 3 shared Manjari GuptaiD· 3 shared Parimal Kumar DasiD· 3 shared Shweta SinghiD· 3 shared Sukhad KuraliD· 3 shared Sameer TrivediiD· 2 shared

Activity by Year

2023-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 44 mutual co-author links

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3 shared papersMolecular Biology

Abhay Kumar PathakORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Non-Invasive Diagnostic Evaluation of Urinary Exosomal Let-7c Cluster Expression in Bladder Cancer Using Machine Learning Approaches

Sukhad Kural, Lalit Kumar, Abhay Kumar Pathak, Shweta Singh, Garima Jain, Mahima Yadav, Yashasvi Singh, Ujwal Kumar, Sameer Trivedi, Manjari Gupta, Sakshi Agarwal, Vibhav Gautam, Parimal Kumar Das

This study evaluates the diagnostic potential of urinary exosomal let-7c cluster miRNAs in bladder cancer using machine learning models, finding significant differentiation between cancer and healthy controls with high accuracy.

BMC Cancer · Jul 21, 2026Peer-reviewedMolecular Biology

miRNA Biomarkers in Prostate Cancer: Leveraging Machine Learning for Improved Diagnostic Accuracy

Shweta Singh, Abhay Kumar Pathak, Sukhad Kural, Lalit Kumar, Madan Gopal Bhardwaj, Mahima Yadav, Sameer Trivedi, Parimal Kumar Das, Manjari Gupta, Garima Jain

This study uses machine learning to analyze miRNA expression in blood samples to improve prostate cancer diagnosis, achieving 77.42% accuracy and reducing reliance on fixed cutoff values.

bioRxiv · Oct 25, 2024 · PreprintGenomics

gQuant: A Robust and Generalizable Algorithm for Identifying Normalizer Genes in qRT-PCR Data: A Case Study on Urinary Exosomal miRNAs

Abhay Kumar Pathak, Sukhad Kural, Shweta Singh, Lalit Kumar, Mahima Yadav, Manjari Gupta, Parimal Kumar Das, Garima Jain

gQuant improves normalizer gene identification in qRT-PCR data by using ensemble voting classifiers, showing better consistency and accuracy than existing tools.

bioRxiv · Nov 25, 2023 · PreprintMolecular Biology