L1000CDS2, developed by Ma’ayan Laboratory for the BD2K-LINCS DCIC, queries gene expression signatures against the LINCS L1000 to identify and prioritize small molecules that can reverse or mimic the observed input expression pattern.
The Data Standards page has been updated to reflect the most recent standards releases in LINCS Production Phase 2.
LINCS centers recently released the first wave of data which includes RNA-seq, L1000, P100, SWATH, Cell Viability and Growth, KinomeScan, and RPPA profiling human cell lines treated with many drugs and small molecules.
The data releases and milestones page describes the collections of data released and planned to be released to the public by the LINCS consortia.
Workshop: Interdisciplinary Approaches to Biomedical Data Science Challenges: SAMSI Innovations Lab | July 20-24, 2015
Stephan Schurer PhD, BD2K-LINCS Data Coordination and Integration Center, served as a mentor in this workshop to guide scientists in the formation of interdisciplinary projects aimed at developing models, methods, and approaches to overcome biomedical data science challenges. During the course of the workshop, participants were exposed to LINCS resources. The workshop took place from July 20 to 24, 2015 at the Hamner Conference Center at the NC Biotechnology Center, 15 TW Alexander Drive in Research Triangle Park, North Carolina.
Purpose of this workshop is to bring together (Library of Integrated Network-based Cellular Signatures) LINCS scientists and scientists from the alcohol research community to explore how LINCS resources can facilitate identification of druggable targets and novel and/or repurposed compounds for the treatment of alcohol dependence.
Date | Time | Location
- Friday, June 19, 2015 from 2-5 PM
- Grand Hyatt (Room: Travis C/D), San Antonio, TX
- Please RSVP by May 1, 2015 to Matthew Reilly at email@example.com
- Space is limited to 50 participants
Welcome and Opening Remarks
Matthew Reilly PhD and Ajay Pillai PhD, NIH
Hands-on Session: Web Apps and Tools
Session Leaders: Avi Ma’ayan PhD, BD2K-LINCS Data Coordination and Integration Center and Aravind Subramanian PhD, LINCS Center for Transcriptomics
This session will consist of a hands on demonstration of currently available web apps and tools from the LINCS Common Fund program. Participants will learn how to apply these tools to their own research programs. Please bring your laptop computer and gene expression or other genomic data to analyze.
- Please register and create a lincscloud.org account before the workshop.
- Your genomics datasets you bring to analyze should be formatted either as (1) official gene symbols or (2) Affymetrix U133A probe IDs. Some of the web tools require a list of both up-regulated and down-regulated gene lists and some of the tools only accept gene symbols.
- Because the majority of the LINCS datasets use human cell lines, gene sets should be annotated for mammalian species.
- When you RSVP for the workshop, please indicate your area of expertise: genomics, computational or other.
- Also, if you already have experience with working with any of the LINCS tools, you are welcome to submit questions/concerns, suggestions or other feedback in advance of the workshop. You can submit your questions etc., to the workshop organizer: Matthew Reilly at firstname.lastname@example.org.
The BD2K-LINCS DCIC announces a call for applications for the next round of external data science research projects. The call is for two year projects that would leverage LINCS generated data through application of novel computational methods. For more information, please visit: http://www.lincs-dcic.org/#/edsr. Please visit the funding opportunities page for more details.
LINCS Investigators Present at the AACR Special Conference on Computational and Systems Biology of Cancer
February 8-11, 2015
The Fairmont San Francisco
San Francisco, California
Andrea Califano, Columbia University, New York, New York
Brenda J. Andrews, University of Toronto, Toronto, Ontario, Canada
Peter K. Jackson, Stanford University, Stanford, California
Spatial Systems Biology and Cancer
Joe W. Gray, MEP LINCS Center
Using Single-cell Pharmacology to Improve Drug Design
Peter K. Sorger, HMS LINCS Center
Lean Data Integration Strategy in Cancer Systems Biology and Systems Pharmacology
Avi Ma’ayan, BD2K-LINCS Data Coordination and Integration Center
Transcriptional Landscape of Drug Response Guides the Design of Specific and Potent Drug Combinations
Marc Hafner, HMS LINCS Center
BioGPS Spotlight on the LINCS Information FramEwork (LIFE) which is a novel knowledge-based, extensible information system of interconnected components that leverages semantic-web technologies and domain level ontologies.
The full article is posted here.
12 Big Data to Knowledge Centers of Excellence Funded
Article about the recently funded Big Data to Knowledge Centers of Excellence was published in Biomedical Computation Review. The Data Integration and Cellular Signaling section of the article describes the BD2K-LINCS Data Coordination and Integration Center’s efforts.
The full article is posted here.
News release published by the National Institutes of Health about the Big Data to Knowledge (BD2K) initiative. The BD2K-LINCS Data Coordination and Integration Center is one of the components of the new BD2K awards.
The BD2K-LINCS Data Coordination and Integration Center will be a data coordination center for the NIH Common Fund’s Library of Integrated Network-based Cellular Signatures (LINCS) program, which aims to characterize how a variety of types of cells, tissues and networks respond to disruption by drugs and other factors. The center will support data science research focusing on interpreting and integrating LINCS-generated data from different data types and databases in the LINCS-funded projects. This center is co-funded by BD2K and the NIH Common Fund.
News release published by the National Institutes of Health about the funding of six Data and Signature Generating Centers for the Library of Integrated Network-based Cellular Signatures (LINCS) program.
The LINCS program aims to catalog and analyze cellular function and molecular activity in response to perturbing agents — such as drugs and genetic factors — that are potentially disruptive to cells. LINCS researchers then will measure the cells’ tiniest molecular and biochemical responses, and use computer analyses to uncover common patterns in these responses — called “signatures.” LINCS data will be freely available to any scientist.