Request for Information (RFI): Future Research Priorities for the Common Fund LINCS Program

Notice Number: NOT-RM-13-020

Key Dates
Release Date: May 31, 2013
Response Date:  June 14, 2013

Issued by
National Institutes of Health (NIH)
Office of Strategic Coordination (Common Fund)


The NIH seeks comments regarding the scientific focus of the second phase of the Common Fund’s Library of Integrated Network-based Cellular Signatures (LINCS) program. This Request for Information (RFI) is soliciting information that NIH staff will use to refine the future directions for the LINCS program such that the resources that it generates will be of maximal use for biomedical investigators in their studies of a variety of problems ranging from the determination of disease mechanisms at the molecular level to the development of new therapeutics and/or biomarkers.


The LINCS program aims to create a network-based understanding of biology by cataloging changes in molecular and cellular phenotypes (such as gene expression, protein expression, post-translational modifications, metabolic state, or cell behavior) that occur when cells are exposed to small molecule or genetic perturbations. Computational tools are also being developed to analyze, visualize and integrate these data to generate a public “library” of molecular and cellular signatures that describes how different types of cells respond to various genetic and environmental stressors.  The LINCS project intends to generate a resource that will be used to improve our understanding of cellular pathways and to inform the development of therapies that might restore perturbed pathways and networks to their unperturbed states.  The LINCS program is developing a robust framework for understanding the effects of perturbations on human cells in a standardized, integrated, coordinated and generalizable manner.  For further details about the current organization and accomplishments of LINCS, see

The underlying premise of the LINCS program is that disrupting any one of the many steps of a given biological process will cause related changes in the molecular and cellular characteristics, behavior, and/or function of the cell (known as the cellular phenotype). A useful cellular phenotype will be informative about clinical and disease states. Thus, observing how and when a cell’s phenotype is altered by specific stressors can provide clues about the underlying mechanisms involved in creating a perturbed state and ultimately yield information about the molecular basis of disease etiology. Other uses could include comparing cellular phenotypes to identify common or expected responses.
The LINCS program has been generating data and signatures on a range of cell types since 2011 (  The LINCS data generation centers have used the following assays to profile cellular responses: gene expression has been profiled in around 15 cell types using >10,000 small molecules and about 5000 genetic perturbations; multiplex and multi-assay data (proteomic using reverse phase arrays, imaging and phenotypic assays like ELISA) at multiple time points and at multiple doses; plus dose-response data on cell growth for 70+ kinase inhibitors on 1000 diverse cell lines. In the past year, LINCS has also developed tools to help researchers navigate and discover data of interest. In addition to studying frequently used established human cell lines, LINCS is expanding in a limited way to include primary cells and relevant differentiated cell types derived from patient-specific induced pluripotent stem cells.  LINCS is also supporting new laboratory technology development in order to increase the types of cellular responses measured to include proteomic and metabolomic profiles, as well as exploring synergistic responses to combination drug therapies.

To help ensure that LINCS continues to develop a resource that is optimally useful to the biomedical research community, the NIH wishes to collect information and relevant materials that will help to inform potential future uses and further development of the LINCS program and the data types and analytical tools that it generates.

Information Requested 

This RFI is soliciting feedback from the scientific and bioinformatics research communities, other interested organizations, and the public about the LINCS program as it goes forward, including the critical gaps, challenges and potential opportunities that can now be addressed by this research approach.  Comments can include but are not limited to the following areas:

  • Categorizing your level of familiarity with the LINCS resources into one of three categories: high, low, none.
  • Identifying your field of research and how the LINCS resource may benefit your research.
  • Whether current methods for browsing, accessing, and analyzing LINCS data is optimal for use by biomedical investigators who lack deep computational expertise.
  • Types of LINCS product (e.g. large-scale perturbation-response signatures data, data analysis methods and tools, or technologies developed for data generation) that will be most useful for your future research.  
  • Discussion on future  LINCS focus on investing resources to expand the range and complexity of the assay types, focus on expanding into more complex cell types (e.g., primary cells and iPS and other derived cells), or a balance between these two independent goals..
  • Discussion of the overall impact on the LINCS resource when making choices between kinds of perturbations (moving beyond small molecule and genetic manipulations), assays undertaken at multiple doses and time-points, or studying combinations of perturbations.
  • Discussion of  how LINCS should balance its data generation efforts between performing as many experiments under as many conditions as possible or generating data focused more on direct disease-relevant hypotheses. For example, would you suggest a 50:50 balance between these two types of research efforts, or a ratio that is skewed more toward one area than the other?
  • LINCS resource incorporating LINCS-like perturbation-response signatures from the community going forward.  Response can include the data types that are most amenable, any foreseen challenges, and the identification of appropriate sources for accessing such data.


Response to this RFI is voluntary. All interested parties are invited to respond. Any personal identifiers (e.g. names, addresses, email addresses, etc.) will be removed when responses are compiled. Only the de-identified comments will be used. Proprietary, classified, confidential, or sensitive information should not be included in your response. The United States government reserves the right to use any non-proprietary technical information in any resultant solicitation(s).

This RFI is for information and planning purposes only and should not be construed as a solicitation or as an obligation on the part of the United States government to provide support for any ideas identified in response to it.  Please note that the United States government will not pay for the preparation of any information submitted or for its use of that information.  Responses will be compiled and shared internally with staff from NIH, as appropriate.  

Submitting a Response

Interested extramural investigators and other interested parties are invited to respond.
All comments must be submitted electronically to:  Please limit your responses to two pages.  Responders are free to address any or all of the above items. 
Responses to this RFI will be accepted through Friday June 14, 2013. Responders will receive an electronic confirmation acknowledging receipt of a response, but will not receive individualized feedback on any submissions. No basis for claims against the U.S. Government shall arise as a result of a response to this request for information or from the Government’s use of such information.


Please direct all inquiries to:

Ajay Pillai
5635 Fishers Lane, Suite 4076
Rockville, MD 20852
Telephone: (301) 594-7108

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