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Getting Started with LINCS Datasets and Tools.

Zhuorui Xie1, Eryk Kropiwnicki1, Megan L Wojciechowicz1

  • 1Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, New York.

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Summary
This summary is machine-generated.

The Library of Integrated Network-based Cellular Signatures (LINCS) program generated digital resources to analyze cellular responses. These tools facilitate biological insights and drug discovery from complex biological data.

Keywords:
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Area of Science:

  • * Computational Biology
  • * Systems Biology
  • * Bioinformatics

Background:

  • * The NIH Common Fund's Library of Integrated Network-based Cellular Signatures (LINCS) program aimed to understand human cellular responses to various perturbations.
  • * High-content assays including transcriptomics and proteomics were employed to measure these cellular responses.
  • * The program focused on creating a comprehensive dataset of cellular signatures.

Purpose of the Study:

  • * To detail protocols for processing LINCS data into cellular signatures.
  • * To guide the utilization of LINCS digital resources for hypothesis generation and knowledge discovery.
  • * To facilitate the integration of LINCS data with other public datasets for broader biological insights.

Main Methods:

  • * Development of digital resources by six data and signature generation centers (DSGCs) and one data coordination and integration center (DCIC).
  • * Utilization of tools such as CLUE.io, BioJupies, Appyters, and iLINCS for data analysis and signature generation.
  • * Application of specific assays like L1000, KINOMEscan, and proteomics.

Main Results:

  • * Creation of multiple digital resources, including databases, tools, and workflows, to manage and analyze LINCS data.
  • * Establishment of methods for computing signatures from L1000 data and analyzing gene expression.
  • * Demonstrated utility of resources like L1000FWD for drug discovery and KINOMEscan for target identification.

Conclusions:

  • * The LINCS program successfully generated valuable digital resources and datasets for understanding cellular responses.
  • * These resources empower researchers to derive new biological and pharmacological insights.
  • * The developed protocols and tools accelerate the discovery of novel therapeutics by leveraging integrated biological data.