Rammohan Shukla

This paper develops a low-input polysome profiling protocol for human postmortem brain tissue and adapts it for neuronal cell lines and mouse brain.

This study identifies progressive molecular differences in depression across clinical stages using RNA-seq data, revealing shared and distinct pathways and cell-type-specific changes associated with symptom dimensions and therapeutic targets.

This study shows that low-dose developmental exposure to deltamethrin disrupts molecular pathways related to circadian rhythms and MAP kinase in mouse brains, linking it to ADHD-like behaviors.

This study identifies ribosomal dysregulation as a conserved mechanism in human depression and mouse chronic stress, linking stress-induced changes in ribosomal proteins and pseudogenes to synaptic dysfunction.

This study uses a temporal memory algorithm to model how synaptic atrophy in the neocortex affects predictive capacity and prediction confidence, linking it to major depressive disorder symptoms.

This study investigates the molecular mechanisms of psychological loss in rats using a multi-omics approach, finding changes in microglia and extracellular matrix linked to impaired emotional processing.

The paper uses sn-RNAseq data to identify cell-type-specific vulnerabilities to diseases and drugs in the anterior cingulate cortex, revealing distinct patterns of disease-state and drug effects.

The paper investigates transcriptomic changes in cortical microcircuit cell types under chronic stress and finds coordinated shifts in gene expression patterns associated with altered excitation-inhibition balance.

This study analyzes the proteomic changes in schizophrenia using postmortem brain samples and shows how antipsychotic drugs modulate these changes across multiple biological levels.

The paper integrates transcriptomic data with in-silico analyses to identify cellular, molecular, and causal pathways in trait and state depression.

The paper analyzes transcriptomic data from pilocarpine-induced temporal lobe epilepsy to identify predictive biomarkers and cellular mechanisms, revealing aberrant interactions between cell types and potential drug targets.

This study examines the relationship between astrocyte subtypes, neurological and psychiatric diseases, and psychotropic medications using gene enrichment analysis and qPCR, finding that astrocytes are not a primary target of these medications.

This study compares psychiatric disorders using pathway, cell-type, drug-target, and chromosomal analyses to identify common and distinct features across an unbiased cluster of disorders.

Kaleidoscope is a web application that provides access to omics databases and tools for in silico hypothesis exploration, demonstrating its use with DISC1 gene analysis across multiple datasets.

The paper identifies lamina-specific gene expression changes in pyramidal neurons from schizophrenia patients compared to controls, highlighting immune and synaptic pathway disruptions.

This paper reviews signature-based in silico approaches for drug repurposing in CNS disorders, integrating data science platforms to improve clinical relevance and address regulatory and knowledge challenges.

This study shows that reduced BDNF leads to increased p62 and decreased GABAAR surface expression, contributing to behavioral deficits in mice, and suggests similar changes in human depression.