Talcott, C. | bioRxiv Science

bioRxiv2021

DatumKB: A Database of Biological Experimental Results

1.DatumKB is a freely accessible database of experimental results involving the function and regulation of human proteins in cultured cells. The results are manually curated from biological research literature using a shorthand language and stored as datums. Datums were originally designed to be used as evidence for rules in a Pathway Logic model of intracellular signal transduction (STM8, http://pl.csl.sri.com/online.html) (1). They are independent units that can be understood by biologists, traced back to their source, and have enough structure to be interrogated computationally. The information is expressed using a controlled vocabulary with links to well known databases such as HUGO Gene Nomenclature Committee (HGNC), UniProt, PubChem, and Cellosaurus. DatumKB can be searched using a query interface and the results can be downloaded in the original datum format, a simplified text format, or a JSON file. Links to detailed documentation of datum structure and a tutorial for the search engine are provided. Database URLhttps://datum.csl.sri.com

cell biology↗

bioRxiv2019

Logic-based Analysis of Gene Expression Data Predicts Pathway Crosstalk between TNF, TGFB1 and EGF in Basal-like Breast Cancer

For breast cancer, clinically important subtypes are well characterised at the molecular level in terms of gene expression profiles. In addition, signaling pathways in breast cancer have been extensively studied as therapeutic targets due to their roles in tumor growth and metastasis. However, it is challenging to put signaling pathways and gene expression profiles together to characterise biological mechanisms of breast cancer subtypes since many signaling events result from post-translational modifications, rather than gene expression differences.\n\nWe present a logic-based approach to explain the differences in gene expression profiles among breast cancer subtypes using Pathway Logic and transcriptional network information. Pathway Logic is a rewriting-logic-based formal system for modeling biological pathways including post-translational modifications. Proposed method demonstrated its utility by constructing subtype-specific path from key receptors (TNFR, TGFBR1 and EGFR) to key transcription factor (TF) regulators (RELA, ATF2, SMAD3 and ELK1) and identifying potential pathway crosstalk via TFs in basal-specific paths, which could provide a novel insight on aggressive breast cancer subtypes.\n\nAvailabilityAnalysis result is available at http://epigenomics.snu.ac.kr/PL/

bioinformatics↗