scholarly journals Model organism databases are in jeopardy

Development ◽  
2021 ◽  
Vol 148 (19) ◽  
Author(s):  
Hugo J. Bellen ◽  
E. J. A. Hubbard ◽  
Ruth Lehmann ◽  
Hiten D. Madhani ◽  
Lila Solnica-Krezel ◽  
...  
Keyword(s):  
Model Organism ◽  
Model Organism Databases

scholarly journals Wormicloud: a new text summarization tool based on word clouds to explore the C. elegans literature

Database ◽  
2021 ◽  
Vol 2021 ◽  
Author(s):  
Valerio Arnaboldi ◽  
Jaehyoung Cho ◽  
Paul W Sternberg
Keyword(s):  
Search Engines ◽  
Complex Structure ◽  
Model Organism ◽  
Gene Interaction ◽  
Relevant Information ◽  
Biomedical Literature ◽  
C Elegans ◽  
Word Clouds ◽  
Scientific Papers ◽  
Model Organism Databases

Abstract Finding relevant information from newly published scientific papers is becoming increasingly difficult due to the pace at which articles are published every year as well as the increasing amount of information per paper. Biocuration and model organism databases provide a map for researchers to navigate through the complex structure of the biomedical literature by distilling knowledge into curated and standardized information. In addition, scientific search engines such as PubMed and text-mining tools such as Textpresso allow researchers to easily search for specific biological aspects from newly published papers, facilitating knowledge transfer. However, digesting the information returned by these systems—often a large number of documents—still requires considerable effort. In this paper, we present Wormicloud, a new tool that summarizes scientific articles in a graphical way through word clouds. This tool is aimed at facilitating the discovery of new experimental results not yet curated by model organism databases and is designed for both researchers and biocurators. Wormicloud is customized for the Caenorhabditis  elegans literature and provides several advantages over existing solutions, including being able to perform full-text searches through Textpresso, which provides more accurate results than other existing literature search engines. Wormicloud is integrated through direct links from gene interaction pages in WormBase. Additionally, it allows analysis on the gene sets obtained from literature searches with other WormBase tools such as SimpleMine and Gene Set Enrichment. Database URL: https://wormicloud.textpressolab.com

scholarly journals Alliance of Genome Resources Portal: unified model organism research platform

2019 ◽  
Vol 48 (D1) ◽  
pp. D650-D658 ◽  
Author(s):  
◽  
Julie Agapite ◽  
Laurent-Philippe Albou ◽  
Suzi Aleksander ◽  
Joanna Argasinska ◽  
...  
Keyword(s):  
Gene Ontology ◽  
Model Organism ◽  
Model Organisms ◽  
Data Types ◽  
Primary Model ◽  
Genomic Studies ◽  
Health And Disease ◽  
Extensive Body ◽  
Access To Data ◽  
Model Organism Databases

Abstract The Alliance of Genome Resources (Alliance) is a consortium of the major model organism databases and the Gene Ontology that is guided by the vision of facilitating exploration of related genes in human and well-studied model organisms by providing a highly integrated and comprehensive platform that enables researchers to leverage the extensive body of genetic and genomic studies in these organisms. Initiated in 2016, the Alliance is building a central portal (www.alliancegenome.org) for access to data for the primary model organisms along with gene ontology data and human data. All data types represented in the Alliance portal (e.g. genomic data and phenotype descriptions) have common data models and workflows for curation. All data are open and freely available via a variety of mechanisms. Long-term plans for the Alliance project include a focus on coverage of additional model organisms including those without dedicated curation communities, and the inclusion of new data types with a particular focus on providing data and tools for the non-model-organism researcher that support enhanced discovery about human health and disease. Here we review current progress and present immediate plans for this new bioinformatics resource.

Model Organism Databases in Behavioral Neuroscience

2012 ◽  
pp. 25-46
Author(s):  
Mary. Shimoyama ◽  
Jennifer R. Smith ◽  
G. Thomas. Hayman ◽  
Victoria. Petri ◽  
Rajni. Nigam
Keyword(s):  
Model Organism ◽  
Behavioral Neuroscience ◽  
Model Organism Databases

scholarly journals WholeCellKB: model organism databases for comprehensive whole-cell models

2012 ◽  
Vol 41 (D1) ◽  
pp. D787-D792 ◽  
Author(s):  
Jonathan R. Karr ◽  
Jayodita C. Sanghvi ◽  
Derek N. Macklin ◽  
Abhishek Arora ◽  
Markus W. Covert
Keyword(s):  
Model Organism ◽  
Cell Models ◽  
Whole Cell ◽  
Model Organism Databases

scholarly journals The Quest for Orthologs benchmark service and consensus calls in 2020

2020 ◽  
Vol 48 (W1) ◽  
pp. W538-W545 ◽  
Author(s):  
Adrian M Altenhoff ◽  
Javier Garrayo-Ventas ◽  
Salvatore Cosentino ◽  
David Emms ◽  
Natasha M Glover ◽  
...  
Keyword(s):  
Comparative Genomics ◽  
Common Ancestor ◽  
Computational Cost ◽  
Model Organism ◽  
Ground Truth ◽  
Last Common Ancestor ◽  
Common Input ◽  
Reference Set ◽  
Input Dataset ◽  
Model Organism Databases

Abstract The identification of orthologs—genes in different species which descended from the same gene in their last common ancestor—is a prerequisite for many analyses in comparative genomics and molecular evolution. Numerous algorithms and resources have been conceived to address this problem, but benchmarking and interpreting them is fraught with difficulties (need to compare them on a common input dataset, absence of ground truth, computational cost of calling orthologs). To address this, the Quest for Orthologs consortium maintains a reference set of proteomes and provides a web server for continuous orthology benchmarking (http://orthology.benchmarkservice.org). Furthermore, consensus ortholog calls derived from public benchmark submissions are provided on the Alliance of Genome Resources website, the joint portal of NIH-funded model organism databases.

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