Imperial College London


Faculty of MedicineNational Heart & Lung Institute

Lecturer in Cardiovascular Bioinformatics and Medical Statis







Isle 9, SouthICTEM buildingHammersmith Campus





The primary focus of my research for past 8 years has been to understand the transcriptional and post-transcriptional regulation of gene-expression. I have developed frameworks for integrating epigenetic changes with gene-expression. My present work applies system genetics approaches to the discovery of disease pathways and their master regulation. Briefly, my work integrates genome-wide information relating to genetic and epigenetic variation with the gene expression data (using RNA-Seq) and phenotypes to map molecular mechanisms of disease.  In my current work with Drs Johnson and Petretto, funded by UCB Pharma, I characterised differentially co-expressed gene networks between healthy and epileptic brain and mapped the genetic regulation for these dysregulated networks. Using integrative approaches, I prioritized gene network that were enriched for neuroinflammatory pathways as having a causal relationship to epilepsy, and using logical reasoning approaches we identified regulators of a key pathway leading directly to a potential new drug discovery in epilepsy. Although, this project is specific for epilepsy, the modelling approaches involved can be generalised to any biological system including more widely for disorders of the human brain.

Selected Publications

Journal Articles

Laaniste L, Srivastava P, Stylianou T, et al., 2019, Integrated systems-genetic analyses reveal a network target for delaying glioma progression, Annals of Clinical and Translational Neurology, Vol:6, ISSN:2328-9503, Pages:1616-1638

Srivastava P, van Eyll J, Godard P, et al., 2018, A systems-level framework for drug discovery identifies Csf1R as an anti-epileptic drug target, Nature Communications, Vol:9, ISSN:2041-1723

Srivastava PK, Bagnati M, Delahaye-Duriez A, et al., 2017, Genome-wide analysis of differential RNA editing in epilepsy, Genome Research, Vol:27, ISSN:1549-5469, Pages:440-450

Delahaye-Duriez A, Srivastava P, Shkura K, et al., 2016, Rare and common epilepsies converge on a shared gene regulatory network providing opportunities for novel antiepileptic drug discovery, Genome Biology, Vol:17, ISSN:1474-760X

Johnson MR, Shkura K, Langley SR, et al., 2016, Systems genetics identifies a convergent gene network for cognition and neurodevelopmental disease, Nature Neuroscience, Vol:19, ISSN:1546-1726, Pages:223-232

Rotival M, Ko J-H, Srivastava PK, et al., 2015, Integrating phosphoproteome and transcriptome reveals new determinants of macrophage multinucleation, Molecular & Cellular Proteomics, Vol:14, ISSN:1535-9476, Pages:484-498

Johnson MR, Behmoaras J, Bottolo L, et al., 2015, Systems genetics identifies Sestrin 3 as a regulator of a proconvulsant gene network in human epileptic hippocampus., Nat Commun, Vol:6

Srivastava PK, Moturu T, Pandey P, et al., 2014, A comparison of performance of plant miRNA target prediction tools and the characterization of features for genome-wide target prediction, BMC Genomics, Vol:15, ISSN:1471-2164, Pages:348-348

Srivastava P, Mangal M, Agarwal SM, 2014, Understanding the transcriptional regulation of cervix cancer using microarray gene expression data and promoter sequence analysis of a curated gene set, Gene, Vol:535, ISSN:0378-1119, Pages:233-238

Srivastava PK, Hull RP, Behmoaras J, et al., 2013, JunD/AP1 regulatory network analysis during macrophage activation in a rat model of crescentic glomerulonephritis, BMC Systems Biology, Vol:7, ISSN:1752-0509

Hull RP, Srivastava PK, D'Souza Z, et al., 2013, Combined ChIP-Seq and transcriptome analysis identifies AP-1/JunD as a primary regulator of oxidative stress and IL-1 beta synthesis in macrophages, BMC Genomics, Vol:14, ISSN:1471-2164

Feuerborn A, Srivastava PK, Küffer S, et al., 2011, The Forkhead factor FoxQ1 influences epithelial differentiation., J Cell Physiol, Vol:226, Pages:710-719

Srivastava PK, Küffer S, Brors B, et al., 2008, A cut-off based approach for gene expression analysis of formalin-fixed and paraffin-embedded tissue samples., Genomics, Vol:91, Pages:522-529

Srivastava PK, Desai DK, Nandi S, et al., 2007, HMM-ModE--improved classification using profile hidden Markov models by optimising the discrimination threshold and modifying emission probabilities with negative training sequences., Bmc Bioinformatics, Vol:8

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