InterMine: a flexible data warehouse system for the integration and analysis of heterogeneous biological data

Smith, Richard N.; Aleksić, J.; Butano, Daniela; Carr, Adrian R.; Contrino, Sergio; Hu, Fengyuan; Lyne, Mike; Lyne, Rachel; Kalderimis, Alex; Rutherford, Kim; Stepan, Radek; Sullivan, Julie; Wakeling, Matthew; Watkins, Xavier; Micklem, Gos

doi:10.1093/bioinformatics/bts577

Cited by 232 publications

(205 citation statements)

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“…Another set of important tools to mine a variety of databases are the InterMine [ 36 ] powered databases such a FlyMine [ 37 ], ModMine [ 38 ], YeastMine [ 39 ] and others. InterMine databases can be mined with powerful queries that can be customized completely by users.…”

Section: What Network Approaches Are Currently Being Used To Study Ad?mentioning

confidence: 99%

Network Approaches to the Understanding of Alzheimer’s Disease: From Model Organisms to Humans

Yerbury

Bean

Favrin

2016

Systems Biology of Alzheimer's Disease

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It is becoming increasingly evident that Alzheimer's disease cannot be considered as the outcome of a single pathway, but rather we should view it as a system, that is, a network of interactions between large numbers of different protein molecules. In the last few years, probably because of the inherent limitations of traditional methods and because of the great increase in availability of sequencing data, this type of approach is being used more and more. In the following, we will discuss what constitutes a "network approach," what are its pros and cons, a number of recent case studies and finally what are the future perspectives of this type of analysis.

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Section: What Network Approaches Are Currently Being Used To Study Ad?mentioning

confidence: 99%

Network Approaches to the Understanding of Alzheimer’s Disease: From Model Organisms to Humans

Yerbury

Bean

Favrin

2016

Systems Biology of Alzheimer's Disease

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“…The targeted genes are associated with Him phenotypes in mutant or RNAi-treated animals. The phenotypic information was obtained from publications and data sets deposited online using WormMart and WormMine data mining tools and literature search features in Wormbase: (releases WS232-240) and the literature search tools of PubMed: www.ncbi.nlm.nih.gov [13,14], including the RNAi database: http://aquila.bio.nyu.edu/cgi-bin/ rnaidb/index.cgi [15]. Insert sizes were verified by PCR.…”

Section: Rnai Delivery Using Bacterial ''Feeding''mentioning

confidence: 99%

Systematic comparison of bacterial feeding strains for increased yield of Caenorhabditis elegans males by RNA interference‐induced non‐disjunction

et al. 2014

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Edited by Ned ManteiKeywords: RNAi Caenorhabditis elegans males Non-disjunction Kinesin-like protein Him phenotype dsRNA a b s t r a c t Rare Caenorhabditis elegans males arise when sex chromosome non-disjunction occurs during meiosis in self-fertilizing hermaphrodites. Non-disjunction is a relatively rare event, and males are typically observed at a frequency of less than one in five hundred wild-type animals. Males are required for genetic crosses and phenotypic analysis, yet current methods to generate large numbers of males can be cumbersome. Here, we identify RNAi reagents (dsRNA-expressing bacteria) with improved effectiveness for eliciting males. Specifically, we used RNAi to systematically reduce the expression of over two hundred genes with meiotic chromosome segregation functions, and we identified a set of RNAi reagents that robustly and reproducibly elicited male progeny.

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“…Some attempts to go beyond the drawbacks of a handcrafted combination of different resources have already been made. HumanMine [1], Java BioWareHouse [2], and Bio4J [3] are some examples of such tools. Regardless of focus and biological data sources considered by them (and also by others), they all lack one or more high-level functional features, such as web interface availability, dynamic data visualization, custom queries support, analytics, and expandability.…”

Section: Introductionmentioning

confidence: 99%

Querying and analyzing biological data with BioGraph

Messina

Fiannaca

Paglia

et al. 2017

Preprint

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Nowadays, a huge amount of biomedical data of different biological entities is provided by many online databases and services, each with its own data model, user interface and query language. However, typical bioinformatics scenarios require the use of more than one resource. Therefore, the availability of a single bioinformatics platform that integrates many biological resources and services is a fundamental issue. Some attempts to go beyond the drawbacks of a handcrafted combination of different resources have already been made. Regardless of focus and considered biological data sources, existing tools lack one or more high-level functional features, such as web interface availability, dynamic data visualization, custom queries support, analytics, and expandability. Here, we present BioGraph, a web application that allows to query, visualize and analyze biological data belonging to several online available resources. BioGraph is built on top of our previously developed graph database called BioGraphDB, which collects and integrates heterogeneous biological data and makes them available through a common structure and Gremlin as unique query language. BioGraph makes use of state-of-the-art technologies and provides some pre-compiled bioinformatics scenarios, as well as the possibility to perform custom queries and obtaining an interactive and dynamic visualization of results.

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InterMine: a flexible data warehouse system for the integration and analysis of heterogeneous biological data

Cited by 232 publications

References 10 publications

Network Approaches to the Understanding of Alzheimer’s Disease: From Model Organisms to Humans

Network Approaches to the Understanding of Alzheimer’s Disease: From Model Organisms to Humans

Systematic comparison of bacterial feeding strains for increased yield of Caenorhabditis elegans males by RNA interference‐induced non‐disjunction

Querying and analyzing biological data with BioGraph

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