Pavlidis, Paul

Coexpression Analysis of Human Genes Across Many Microarray Data Sets

Lee, H. K., Hsu, A. K., Sajdak, J., Qin, J., & Pavlidis, P. (2004) · Genome Research

Bioinformatics and Genomic NetworksGene expression and cancer classification

Cited by 770

Altered brain microRNA biogenesis contributes to phenotypic deficits in a 22q11-deletion mouse model

Stark, K. L., Xu, B., Bagchi, A., Lai, W.-S., Liu, H., Hsu, R., Wan, X., Pavlidis, P., Mills, A. A., Karayiorgou, M., et al. (2008) · Nature Genetics

Genomic variations and chromosomal abnormalitiesMicroRNA in disease regulation

Cited by 648

Molecular and Functional Heterogeneity of Hyperpolarization-Activated Pacemaker Channels in the Mouse CNS

Santoro, B., Chen, S., Lüthi, A., Pavlidis, P., Shumyatsky, G. P., Tibbs, G. R., & Siegelbaum, S. A. (2000) · The Journal of Neuroscience

Ion channel regulation and functionCardiac electrophysiology and arrhythmias

Cited by 600

Single-nucleus transcriptomics of the prefrontal cortex in major depressive disorder implicates oligodendrocyte precursor cells and excitatory neurons

Nagy, C., Maitra, M., Tanti, A., Suderman, M., Théroux, J.-F., Davoli, M. A., Perlman, K., Yerko, V., Wang, Y. C., Tripathy, S. J., et al. (2020) · Nature Neuroscience

Treatment of Major DepressionSingle-cell and spatial transcriptomics

Cited by 532

miR-1202 is a primate-specific and brain-enriched microRNA involved in major depression and antidepressant treatment

Lopez, J. P., Lim, R., Cruceanu, C., Crapper, L., Fasano, C., Labonte, B., Maussion, G., Yang, J. P., Yerko, V., Vigneault, E., et al. (2014) · Nature Medicine

Treatment of Major DepressionMicroRNA in disease regulation

Cited by 308

Molecular aging in human prefrontal cortex is selective and continuous throughout adult life

Erraji-Benchekroun, L., Underwood, M. D., Arango, V., Galfalvy, H., Pavlidis, P., Smyrniotopoulos, P., Mann, J. J., & Sibille, E. (2005) · Biological Psychiatry

Genetics, Aging, and Longevity in Model OrganismsSingle-cell and spatial transcriptomics

Cited by 236

Can we predict protein from mRNA levels?

Fortelny, N., Overall, C. M., Pavlidis, P., & Freue, G. V. C. (2017) · Nature

Breast Cancer Treatment StudiesGene expression and cancer classification

Cited by 217

“Guilt by Association” Is the Exception Rather Than the Rule in Gene Networks

Gillis, J., & Pavlidis, P. (2012) · PLoS Computational Biology

Bioinformatics and Genomic NetworksGene Regulatory Network Analysis

Cited by 214

Altered hippocampal transcript profile accompanies an age-related spatial memory deficit in mice

Verbitsky, M., Yonan, A. L., Malleret, G., Kandel, E. R., Gilliam, T. C., & Pavlidis, P. (2004) · Learning & Memory

Memory and Neural MechanismsNeurogenesis and neuroplasticity mechanisms

Cited by 158

Predictability of human differential gene expression

Crow, M., Lim, N., Ballouz, S., Pavlidis, P., & Gillis, J. (2019) · Proceedings of the National Academy of Sciences

Gene expression and cancer classificationBioinformatics and Genomic Networks

Cited by 117

EGAD: ultra-fast functional analysis of gene networks

Ballouz, S., Weber, M., Pavlidis, P., & Gillis, J. (2017) · Bioinformatics

Bioinformatics and Genomic NetworksGene Regulatory Network Analysis

Cited by 74

Transcriptomic correlates of neuron electrophysiological diversity

Tripathy, S. J., Toker, L., Li, B., Crichlow, C.-L., Tebaykin, D., Mancarci, B. O., & Pavlidis, P. (2017) · PLOS Computational Biology

Single-cell and spatial transcriptomicsNeuroscience and Neuropharmacology Research

Cited by 69

Meta-analysis of gene coexpression networks in the post-mortem prefrontal cortex of patients with schizophrenia and unaffected controls

Mistry, M., Gillis, J., & Pavlidis, P. (2013) · BMC Neuroscience

Schizophrenia research and treatmentBioinformatics and Genomic Networks

Cited by 59

Assessing Transcriptome Quality in Patch-Seq Datasets

Tripathy, S. J., Toker, L., Bomkamp, C., Mancarci, B. O., Belmadani, M., & Pavlidis, P. (2018) · Frontiers in Molecular Neuroscience

Single-cell and spatial transcriptomicsMolecular Biology Techniques and Applications

Cited by 39

Modeling sources of interlaboratory variability in electrophysiological properties of mammalian neurons

Tebaykin, D., Tripathy, S. J., Binnion, N., Li, B., Gerkin, R. C., & Pavlidis, P. (2018) · Journal of Neurophysiology

Neuroscience and Neuropharmacology ResearchIon channel regulation and function

Cited by 15