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Call for Papers - High-Content Imaging and Informatics

A Joint Special Issue with Society for Biomolecular Imaging and Informatics and SLAS

Proposals accepted until November 15, 2019!

Submit Proposals here

SLAS Discovery Guest Editors Paul A. Johnston, Ph.D., (University of Pittsburgh School of Pharmacy) and Myles Fennel, Ph.D., (Arvinas) invite the submission of abstracts pertaining to high-content imaging (HCI) and informatics for publication in a 2020 joint special issue with the Society for Biomolecular Imaging and Informatics (SBI2). Manuscript proposals (abstracts) will be used to select and invite papers for review and publication consideration.

Since 2012, SBI2 has collaborated with SLAS to hold special interest group discussions on selected high-content screening and analysis topics. Drs. Johnston and Fennel are past and current presidents of SBI2, an international community of leaders, scientists and students promoting technological advancement, discovery and education to quantitatively interrogate biological models to provide high context information at the cellular level.

Multiparameter quantitative information extracted from digital images of cells acquired on automated HCI platforms is driving a revolution in phenotypic drug discovery. HCI approaches have progressed beyond specific target readouts to more complex and physiologically relevant cellular models, where data from hundreds to thousands of features are used to define and/or discriminate amongst cellular phenotypes at the individual cell and/or population levels. Artificial intelligence/machine learning approaches such as deep learning that bypass traditional image segmentation methods are being deployed to extract phenotypic information and interrogate the consequences of compound exposure for drug discovery purposes.  

Drs. Johnston and Fennel seek high-quality, short- or full-length research reports, reviews and perspectives related to all aspects of HCI applications. Manuscript proposals (abstracts) are welcome from academia, industry and vendors. Areas of particular interest include, but are not limited to:

  • Complex and physiologically relevant cellular models enabled by HCI
  • Novel reagents, staining technologies and imaging modalities
  • Improved image analysis algorithms, multivariant analysis and informatics tools
  • High-content phenotypic screening case histories
  • 3D models and digital histology/pathology
  • Artificial intelligence/machine learning approaches to HCI drug discovery  

Submit your manuscript proposal before November 15, 2019. It should include your name, contact information, affiliation, a working title and abstract (250-500 words) as an MS Word document.

Invited manuscripts will need to be completed and submitted by January 1, 2020. All submitted papers will be subject to peer-review to ensure scientific rigor, clarity of expression and integration with other contributions in the SLAS Discovery Special Issue. Submissions from SBI2 members, SLAS members, and nonmembers are welcomed!

Publication note: After submissions are accepted, they typically publish online ahead-of-print within 30 days and become immediately searchable and citable with a DOI.

Questions? Please e-mail or call +1.630.256.7527, ext. 106.