Arjun Krishnan
Affiliations: | 2011-2016 | Computational Math, Sci Egr | Michigan State University, East Lansing, MI |
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"Arjun Krishnan"Parents
Sign in to add mentor| Andy Pereira | grad student | 2006-2010 | Virginia Tech |
| Olga G. Troyanskaya | post-doc | 2011-2016 | Michigan State |
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Publications
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| Gomez-Cano F, Rodriguez J, Zhou P, et al. (2024) Prioritizing Metabolic Gene Regulators through Multi-Omic Network Integration in Maize. Biorxiv : the Preprint Server For Biology |
| Palande S, Kaste JAM, Roberts MD, et al. (2023) Topological data analysis reveals a core gene expression backbone that defines form and function across flowering plants. Plos Biology. 21: e3002397 |
| Mancuso CA, Bills PS, Krum D, et al. (2022) GenePlexus: a web-server for gene discovery using network-based machine learning. Nucleic Acids Research |
| Johnson KA, Krishnan A. (2022) Robust normalization and transformation techniques for constructing gene coexpression networks from RNA-seq data. Genome Biology. 23: 1 |
| Mancuso CA, Canfield JL, Singla D, et al. (2020) A flexible, interpretable, and accurate approach for imputing the expression of unmeasured genes. Nucleic Acids Research |
| Liu R, Mancuso CA, Yannakopoulos A, et al. (2020) Supervised-learning is an accurate method for network-based gene classification. Bioinformatics (Oxford, England) |
| Lee YS, Krishnan A, Oughtred R, et al. (2019) A Computational Framework for Genome-wide Characterization of the Human Disease Landscape. Cell Systems |
| Iyer J, Singh MD, Jensen M, et al. (2018) Pervasive genetic interactions modulate neurodevelopmental defects of the autism-associated 16p11.2 deletion in Drosophila melanogaster. Nature Communications. 9: 2548 |
| Wong AK, Krishnan A, Troyanskaya OG. (2018) GIANT 2.0: genome-scale integrated analysis of gene networks in tissues. Nucleic Acids Research |
| Rangan AV, McGrouther CC, Kelsoe J, et al. (2018) A loop-counting method for covariate-corrected low-rank biclustering of gene-expression and genome-wide association study data. Plos Computational Biology. 14: e1006105 |