<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/2422?offset=550 https://bioinformaticsonline.com/bookmarks/view/35131/giggle-a-search-engine-for-large-scale-integrated-genome-analysis Wed, 10 Jan 2018 03:10:45 -0600 https://bioinformaticsonline.com/bookmarks/view/35131/giggle-a-search-engine-for-large-scale-integrated-genome-analysis <![CDATA[GIGGLE: a search engine for large-scale integrated genome analysis]]> GIGGLE is a genomics search engine that identifies and ranks the significance of genomic loci shared between query features and thousands of genome interval files. GIGGLE (https://github.com/ryanlayer/giggle) scales to billions of intervals and is over three orders of magnitude faster than existing methods. Its speed extends the accessibility and utility of resources such as ENCODE, Roadmap Epigenomics, and GTEx by facilitating data integration and hypothesis generation.

https://www.nature.com/articles/nmeth.4556

Address of the bookmark: https://github.com/ryanlayer/giggle

]]> Jit https://bioinformaticsonline.com/bookmarks/view/42645/mmseqs2-ultra-fast-and-sensitive-sequence-search-and-clustering-suite Mon, 18 Jan 2021 10:47:56 -0600 https://bioinformaticsonline.com/bookmarks/view/42645/mmseqs2-ultra-fast-and-sensitive-sequence-search-and-clustering-suite <![CDATA[MMseqs2: ultra fast and sensitive sequence search and clustering suite]]> MMseqs2 (Many-against-Many sequence searching) is a software suite to search and cluster huge protein and nucleotide sequence sets. MMseqs2 is open source GPL-licensed software implemented in C++ for Linux, MacOS, and (as beta version, via cygwin) Windows. The software is designed to run on multiple cores and servers and exhibits very good scalability. MMseqs2 can run 10000 times faster than BLAST. At 100 times its speed it achieves almost the same sensitivity. It can perform profile searches with the same sensitivity as PSI-BLAST at over 400 times its speed.

Address of the bookmark: https://github.com/soedinglab/MMseqs2

]]> Manisha Mishra https://bioinformaticsonline.com/bookmarks/view/44301/carrot2-clustering-engine Fri, 07 Apr 2023 13:11:24 -0500 https://bioinformaticsonline.com/bookmarks/view/44301/carrot2-clustering-engine <![CDATA[Carrot2 clustering engine]]>  

This is the demo application of the Carrot2 clustering engine. It uses Carrot2's algorithms to organize search results into thematic folders.

User interfaces

  • Web Search Clustering organizes search results from public search engines into clusters; offers treemap- and pie-chart visualizations of the clusters.
  • Clustering Workbench clusters content from local files in JSON or Excel format, Solr or Elasticsearch; allows tuning of clustering parameters and exporting results as Excel or JSON.

Search engines

  • Web: web search results provided by etools.ch. Extensive use may require special arrangements with the owner of the etools.ch service.
  • PubMed: abstracts of medical papers from the PubMed database provided by NCBI.
  • Local file: content read from a local file in Carrot2 XML, JSON, CSV or Excel format.
  • Solr: queries an Apache Solr instance.
  • Elasticsearch: queries an Elasticsearch instance.

Clustering algorithms

  • Lingo: creates well-described flat clusters. Does not scale beyond a few thousand search results. Available as part of the open source Carrot2 framework.
  • STC: the classic search results clustering algorithm. Produces flat cluster with adequate description, very fast. Available as part of the open source Carrot2 framework
  • k-means: base line clustering algorithm, produces bag-of-words style cluster descriptions. Available as part of the open source Carrot2 framework

Address of the bookmark: https://search.carrot2.org/#/search/web

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