Author

Daksh P.S. Pamar

Ludwig-Maximilians-Universität München

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 Microbiology· 1

Signature Assays, Organisms & Methods

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Research Focus:drug response / drug discovery· 2 Assay:bulk RNA-seq· 1 Approach:deep learning· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Research Focus:variant effect prediction· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Diyuan LuiD· 2 shared Michael P. MendeniD· 2 shared Alexander J. OhnmachtiD· 1 shared Atefeh KazeroonianiD· 1 shared Beate Spießberger· 1 shared Christian SchulziD· 1 shared Florent AilloudiD· 1 shared Ginte KutkaiteiD· 1 shared

Activity by Year

2024-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

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2 shared papersMicrobiology

Diyuan LuORCID

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2 papers

Recent·Most cited

Decoding Helicobacter pylori Resistance: Machine Learning Enhanced Prediction of Antibiotic Susceptibility using Whole-Genome Sequencing

Florent Ailloud, Diyuan Lu, Beate Spießberger, Daksh P.S. Pamar, Atefeh Kazeroonian, Michael Floßdorf, Mónica Oleastro, Christian Schulz, Markus Gerhard, Michael P. Menden, Sebastian Suerbaum

This study uses machine learning to improve metronidazole resistance prediction in Helicobacter pylori using whole-genome sequencing, achieving better accuracy than traditional methods.

bioRxiv · Aug 7, 2025 · PreprintMicrobiology

Enhancing Gene Expression Representation and Drug Response Prediction with Data Augmentation and Gene Emphasis

Diyuan Lu, Daksh P.S. Pamar, Alexander J. Ohnmacht, Ginte Kutkaite, Michael P. Menden

This paper introduces GExMix, a data augmentation method for gene expression data, which improves drug response prediction by enhancing representation learning and prioritizing gene-centric information.

bioRxiv · May 15, 2024 · PreprintBioinformatics