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Open AccessJournal ArticleDOI

A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles.

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TLDR
The expanded CMap is reported, made possible by a new, low-cost, high-throughput reduced representation expression profiling method that is shown to be highly reproducible, comparable to RNA sequencing, and suitable for computational inference of the expression levels of 81% of non-measured transcripts.
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This article is published in Cell.The article was published on 2017-11-30 and is currently open access. It has received 1943 citations till now.

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Posted ContentDOI

Unveiling the molecular basis of disease co-occurrence: towards personalized comorbidity profiles

TL;DR: A disease interaction network inferred from similarities in patients’ molecular profiles is presented, which significantly recapitulates epidemiologically documented comorbidities, providing the basis for their interpretation at a molecular level.
Book ChapterDOI

Drug Repurposing From Transcriptome Data: Methods and Applications

TL;DR: This chapter will describe in detail the main methods, applications, and computational resources for drug repositioning from transcriptome data, the type of data that has made the most progress in the field.
Posted ContentDOI

Detecting fabrication in large-scale molecular omics data

TL;DR: Methods of fabrication detection in biomedical research are developed and it is shown that machine learning can be used to detect fraud in large-scale omic experiments.
Journal ArticleDOI

Dissection of multiple sclerosis genetics identifies B and CD4+ T cells as driver cell subsets

TL;DR: In this article , the authors used chromatin accessibility data across hematopoietic cells to identify cell type-specific enrichments of MS genetic signals and found that CD4 T and B cells are independently enriched for MS genetics and further refined the driver subsets to T h 17 and memory B cells, respectively.
Journal ArticleDOI

CCSynergy: an integrative deep-learning framework enabling context-aware prediction of anti-cancer drug synergy

TL;DR: In this article , a flexible, context aware and integrative deep-learning framework is proposed for predicting drug synergy in cancer cell lines, based on the Chemical Checker extended drug bioactivity profiles.
References
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Journal Article

Visualizing Data using t-SNE

TL;DR: A new technique called t-SNE that visualizes high-dimensional data by giving each datapoint a location in a two or three-dimensional map, a variation of Stochastic Neighbor Embedding that is much easier to optimize, and produces significantly better visualizations by reducing the tendency to crowd points together in the center of the map.
Journal ArticleDOI

Gene Expression Omnibus: NCBI gene expression and hybridization array data repository

TL;DR: The Gene Expression Omnibus (GEO) project was initiated in response to the growing demand for a public repository for high-throughput gene expression data and provides a flexible and open design that facilitates submission, storage and retrieval of heterogeneous data sets from high-power gene expression and genomic hybridization experiments.
Journal ArticleDOI

BLAT—The BLAST-Like Alignment Tool

TL;DR: How BLAT was optimized is described, which is more accurate and 500 times faster than popular existing tools for mRNA/DNA alignments and 50 times faster for protein alignments at sensitivity settings typically used when comparing vertebrate sequences.
Journal ArticleDOI

Adjusting batch effects in microarray expression data using empirical Bayes methods

TL;DR: This paper proposed parametric and non-parametric empirical Bayes frameworks for adjusting data for batch effects that is robust to outliers in small sample sizes and performs comparable to existing methods for large samples.
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