Author

Rohit Nandakumar

Arizona State UniversityORCID 0000-0002-1036-2262Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:human· 2 Assay:metabolomics· 2 Assay:whole-exome sequencing· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:differential expression· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1

Frequent Co-Authors

Beate PeteriD· 2 shared Haiwei GuiD· 2 shared Valentin DinuiD· 2 shared Wendy H. RaskindiD· 2 shared Xiaojian ShiiD· 2 shared Yookyung KimiD· 2 shared Jackson CarrioniD· 1 shared

Activity by Year

2023-2024 · peak 1/yr

Co-Author Collaboration Network

7 top collaborators · 21 mutual co-author links

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2 shared papersBioinformatics

Beate PeterORCID

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintJun 27, 2024

Joint exome and metabolome analysis in individuals with dyslexia: Evidence for associated dysregulations of olfactory perception and autoimmune functions

Rohit Nandakumar, Xiaojian Shi, Haiwei Gu…·Valentin Dinu

This study analyzes exome and metabolome data from individuals with dyslexia to identify associated dysregulations in olfactory perception and immune functions.

DOI 10.1101/2024.06.27.600448

humanwhole-exome sequencing

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BioinformaticsbioRxivPreprintFeb 27, 2023

A data-fusion approach to identifying developmental dyslexia from multi-omics datasets

Jackson Carrion, Rohit Nandakumar, Xiaojian Shi…·Valentin Dinu

This study uses data fusion and machine learning to analyze multi-omics and clinical data, finding that ensemble methods outperform traditional techniques in identifying developmental dyslexia with high accuracy.

DOI 10.1101/2023.02.27.530280

humanbulk RNA-seq

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