resources

The Dark Kinome Knowledgebase - DKK

The Dark Kinase Knowledgebase (the “DKK”) is being developed as a component of the Kinase Data and Resource Generating Center (DRGC) - one of 3 DRGCs supported as part of the Illuminating the Druggable Genome (IDG) Common Fund effort. The goal of the IDG program is to improve our understanding of the properties and functions of proteins that are currently unannotated within the three most commonly drug-targeted protein families: G-protein coupled receptors, ion channels, and protein kinases.

The goal of the DKK is to generate, systematize and disseminate knowledge about dark kinases, biological networks in which they function and connections to cellular phenotypes and human disease. This is being done by (i) establishing a knowledgebase covering the approximately 160 poorly understood “dark kinases”, (ii) distilling primary data into functional biochemical and biological information and promoting further research using genetic and chemical tools, which we are also developing and making available, (iii) placing dark kinases within a new and emerging network-level understanding of cell signaling and physiology and (iv) identifying those dark kinases whose mutation or mis-regulation is associated with human disease, making them possible therapeutic targets.

This work is funded as part of the Illuminating the Druggable Genome Common Fund program - U24-DK116204-01.

The Focal adhesion analysis server - FAAS

FAAS is a webserver implementing a set of computer vision algorithms designed to automatically process time-lapse images of fluorescently labeled focal adhesion proteins in motile cells (though it has been applied to the tracking of other fluorescently-tagged molecules as well). As of January of 2020, nearly 1.8 million images have been processed by outside researchers. The methods associated with the processing have been published in PLOS One and Cell.

Invadopodia Analysis Server - IAS

IAS is the invadopodia analysis webserver, which implements a set of computer vision algorithms designed to automatically identify, track and quantify invadopodia structures in time-lapse image sets. This service has been tested using invadopodia marked with Lifeact-GFP and ECM labeled with RFP, but any invadopodia/ECM marked set of images should work. See the paper below for more details:

Berginski ME, Creed SJ, Cochran S, Roadcap DW, Bear JE, Gomez SM. 2014. Automated analysis of invadopodia dynamics in live cells. PeerJ 2:e462 https://doi.org/10.7717/peerj.462