Author

Suman Sirimulla

The University of Texas at El PasoORCID 0000-0003-4665-6665Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Biophysics· 1 Genetic & Genomic Medicine· 1

Signature Assays, Organisms & Methods

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Research Focus:drug response / drug discovery· 2 Organism:human· 2 Approach:statistical model· 2 Approach:deep learning· 1 Research Focus:differential expression· 1 Approach:experimental assay· 1 Research Focus:gene regulatory network inference· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Andrea AccogliiD· 1 shared Andrew T. Powell· 1 shared Boris KereniD· 1 shared Candace MussiD· 1 shared Christalena SofocleousiD· 1 shared Delphine HéroniD· 1 shared Eirini TsoutsouiD· 1 shared Elvia Padilla· 1 shared

Activity by Year

2019-2025 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 36 mutual co-author links

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1 shared paperGenetic & Genomic Medicine

Andrea AccogliORCID

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3 papers

Recent·Most cited

Genetic & Genomic MedicineThe American Journal of Human GeneticsPeer-reviewedAug 29, 2025

Pathogenic variants in TMEM184B cause a neurodevelopmental syndrome associated with alteration of metabolic signaling

Kimberly A. Chapman, Farid Ullah, Zachary A Yahiku…·Martha R. C. Bhattacharya

The paper identifies pathogenic TMEM184B variants in six pediatric cases and shows they disrupt metabolic signaling and neural development through functional studies in zebrafish and human cells.

2 citations

humanzebrafish

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BioinformaticsbioRxivPreprintOct 31, 2019

KinasepKipred: A Predictive Model for Estimating Ligand-Kinase Inhibitor Constant (pKi).

Govinda KC, Md Mahmudulla Hassan, Suman Sirimulla

The paper develops a machine learning model to predict ligand-kinase inhibitor constants (pKi) using structural and physicochemical features, achieving high correlation and accuracy.

4 citations

machine learning (classical)drug response / drug discovery

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BiophysicsbioRxivPreprintJan 4, 2019

Discovery of New Classes of Glycine transporter 2 (GlyT2) Inhibitors and Study of GlyT2 Selectivity by Combination of Novel Structural Based Virtual Screening Approach and Free Energy Perturbation (FEP+) Calculations

Filip Fratev, Manuel Miranda-Arango, Elvia Padilla, Suman Sirimulla

The paper discovers new GlyT2 inhibitors with high selectivity over GlyT1 using virtual screening and FEP+ calculations, and suggests potential for treating chronic pain and pancreatic cancer.

DOI 10.1101/510487

humanprotein structure

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