ReviewBriefings in bioinformatics2019
Navigating the disease landscape: knowledge representations for contextualizing molecular signatures.
Review in Briefings in bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
7 citing papers in PubMed.
- ProMENDA: an updated resource for proteomic and metabolomic characterization in depression.Translational psychiatry · 2024Article
- Tumor relevant protein functional interactions identified using bipartite graph analyses.Scientific reports · 2021Article
- Drug2ways: Reasoning over causal paths in biological networks for drug discovery.PLoS computational biology · 2020Article
- Data science in neurodegenerative disease: its capabilities, limitations, and perspectives.Current opinion in neurology · 2020Review
- Quantifying mechanisms in neurodegenerative diseases (NDDs) using candidate mechanism perturbation amplitude (CMPA) algorithm.BMC bioinformatics · 2019Article
- Re-curation and rational enrichment of knowledge graphs in Biological Expression Language.Database : the journal of biological databases and curation · 2019Article
- BEL Commons: an environment for exploration and analysis of networks encoded in Biological Expression Language.Database : the journal of biological databases and curation · 2018Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Large amounts of data emerging from experiments in molecular medicine are leading to the identification of molecular signatures associated with disease subtypes. The contextualization of these patterns is important for obtaining mechanistic insight into the aberrant processes associated with a disease, and this typically involves the integration of multiple heterogeneous types of data. In this review, we discuss knowledge representations that can be useful to explore the biological context of molecular signatures, in particular three main approaches, namely, pathway mapping approaches, molecular network centric approaches and approaches that represent biological statements as knowledge graphs. We discuss the utility of each of these paradigms, illustrate how they can be leveraged with selected practical examples and identify ongoing challenges for this field of research.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.