This workshop is dedicated to developing tools/APIs for mapping or synergizing biomedical ontologies in ways that fit the current, modernized, technology era. Conversations will be around the best practices, with an emphasis on collaborative development and dynamic workflows. Read more “WSBO-2021: Synergizing Biomedical Ontologies Workshop 7/14-15”
Although it is still challenging to prevent the transmission of COVID-19, researchers at the University of Miami are using all the strategies they can to fend off the spread. That includes using cutting-edge research to detect SARS-CoV-2—the virus that causes COVID-19—in wastewater*. Read more “Researchers Broaden Tracking of COVID-19 Through Wastewater”
OntoloBridge, a new platform designed to bridge the gap between regular users of controlled scientific vocabularies and the creators of underlying ontologies, has been developed under a collaborative U01 grant by the University of Miami, Stanford University, and Collaborative Drug Discovery (CDD). The novel platform is now available through the BioPortal Ontology Repository. Read more “Novel Platform Connects Users and Developers of Scientific Vocabularies”
Rapid progress in proteomics and large-scale profiling of biological systems at the protein level necessitates the continued development of efficient computational tools for the analysis and interpretation of proteomics data. Here, we present the piNET server that facilitates integrated annotation, analysis and visualization of quantitative proteomics data, with emphasis on PTM networks and integration with the LINCS library of chemical and genetic perturbation signatures in order to provide further mechanistic and functional insights. Read more “piNET: A Versatile Web Platform for Downstream Analysis and Visualization of Proteomics Data”
Abstract The Drug Toxicity Signature Generation Center (DToxS) at the Icahn School of Medicine at Mount Sinai is one of the centers of the NIH Library of Integrated Network-Based Cellular Signatures (LINCS) program. A key aim of DToxS is to generate both proteomic and transcriptomic signatures that can predict adverse effects, especially cardiotoxicity, of kinase inhibitors approved by the Food and Drug Administration. Read more “Protemic Cellular Signatures of Kinase Inhibitor-Induced Cardiotoxicity: Mount Sinai DToxS LINCS Center Dataset”
Transcatheter closure of the left atrial appendage (LAA) for stroke prevention has emerged as an alternative to systemic anticoagulation in patients with atrial fibrillation (AF) and increased stroke risk. Prophylactic occlusion or excision of the LAA during heart surgery in patients with AF has been performed for decades and may be considered in patients undergoing cardiac surgery. Read more “Interventional Treatment of Incomplete Seal After Transcatheter or Surgical Left Atrial Appendage Closure”
The Library of Integrated Network-Based Cellular Signatures (LINCS) is an NIH Common Fund program with the goal of generating a large-scale and comprehensive catalog of perturbation-response signatures by utilizing a diverse collection of perturbations across many model systems and assay types. The LINCS Data Portal (LDP) has been the primary access point for the compendium of LINCS data and has been widely utilized. Read more “LINCS Data Portal 2.0: Next Generation Access Point for Perturbation-Response Signatures”
In past years, medical oncology has witnessed an unprecedented explosion in the understanding of cancer pathophysiology and pathogenesis. With the advancement of next-generation sequencing technologies such as single-cell RNA sequencing, we are better equipped to explore and model complex phenomena such as cancer heterogeneity, resistance, and etiologies at a granular level. Read more “Machine and Deep Learning Approaches for Cancer Drug Repurposing”
Drug discovery is a complex process with many potential pitfalls. To go to market, a drug must undergo extensive preclinical optimization followed by clinical trials to establish its efficacy and minimize toxicity and adverse events. The process can take 10-15 years and command vast research and development resources costing over $1 billion. Read more “Research Techniques Made Simple: Molecular Docking in Dermatology-A Foray into In Silico Drug Discovery”
As more digital resources are produced by the research community, it is becoming increasingly important to harmonize and organize them for synergistic utilization. The findable, accessible, interoperable, and reusable (FAIR) guiding principles have prompted many stakeholders to consider strategies for tackling this challenge. The FAIRshake toolkit was developed to enable the establishment of community-driven FAIR metrics and rubrics paired with manual and automated FAIR assessments. FAIR assessments are visualized as an insignia that can be embedded within digital-resources-hosting websites. Using FAIRshake, a variety of biomedical digital resources were manually and automatically evaluated for their level of FAIRness.
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Clarke DJB, Wang L, Jones A, Wojciechowicz ML, Torre D, Jagodnik KM, Jenkins SL, McQuilton P, Flamholz Z, Silverstein MC, Schilder BM, Robasky K, Castillo C, Idaszak R, Ahalt SC, Williams J, Schurer S, Cooper DJ, de Miranda Azevedo R, Klenk JA, Haendel MA, Nedzel J, Avillach P, Shimoyama ME, Harris RM, Gamble M, Poten R, Charbonneau AL, Larkin J, Brown CT, Bonazzi VR, Dumontier MJ, Sansone SA, Ma’ayan A. FAIRshake: Toolkit to Evaluate the FAIRness of Research Digital Resources. Cell Syst. 2019 Nov 27;9(5):417-421. doi: 10.1016/j.cels.2019.09.011. Epub 2019 Oct 30. PMID: 31677972; PMCID: PMC7316196.