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Steve Horvath

Researcher at University of California, Los Angeles

Publications -  503
Citations -  85293

Steve Horvath is an academic researcher from University of California, Los Angeles. The author has contributed to research in topics: DNA methylation & Epigenetics. The author has an hindex of 114, co-authored 444 publications receiving 65338 citations. Previous affiliations of Steve Horvath include Lubrizol & University of California.

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WGCNA: an R package for weighted correlation network analysis.

TL;DR: The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis that includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software.
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A General Framework for Weighted Gene Co-Expression Network Analysis

TL;DR: A general framework for `soft' thresholding that assigns a connection weight to each gene pair is described and several node connectivity measures are introduced and provided empirical evidence that they can be important for predicting the biological significance of a gene.
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DNA methylation age of human tissues and cell types

TL;DR: It is proposed that DNA methylation age measures the cumulative effect of an epigenetic maintenance system, and can be used to address a host of questions in developmental biology, cancer and aging research.
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An anatomically comprehensive atlas of the adult human brain transcriptome

TL;DR: A transcriptional atlas of the adult human brain is described, comprising extensive histological analysis and comprehensive microarray profiling of ∼900 neuroanatomically precise subdivisions in two individuals, to form a high-resolution transcriptional baseline for neurogenetic studies of normal and abnormal human brain function.
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Transcriptomic analysis of autistic brain reveals convergent molecular pathology

TL;DR: The results provide strong evidence for convergent molecular abnormalities in ASD, and implicate transcriptional and splicing dysregulation as underlying mechanisms of neuronal dysfunction in this disorder.