BOL: Related items

Carrot2 clustering engine

LEGE — Fri, 07 Apr 2023 13:11:24 -0500

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

World of Omics

Rahul Agarwal — Tue, 16 Jul 2013 17:11:48 -0500

How many variants of "omics" techniques presently in use ?

Should you get sequenced? Not all bad genes predict disease

Rahul Agarwal — Thu, 29 Aug 2013 15:10:53 -0500

“What we really don’t know yet is whether the predictive aspects of the genome are going to turn out to be beneficial or potentially harmful”

“As we roll out genomic medicine we are fighting against this society-wide misconception that having the bad gene means you’re going to get the disease. That’s only true in a very few cases.”

Source:Today Health

Address of the bookmark: http://www.today.com/health/should-you-get-sequenced-not-all-bad-genes-predict-disease-8C11017154

Comparison of Short Read De Novo Alignment Algorithms

Rahul Agarwal — Wed, 21 Aug 2013 07:56:01 -0500

Excellent article to introduce different sequencing methods along with tools for de novo assembly of sequencing reads and their relevant references.

Title: Comparison of Short Read De Novo Alignment Algorithms

Author: Nikhil Gopal

Address of the bookmark: http://biochem218.stanford.edu/Projects%202011/Gopal%202011.pdf

Latest paper on comparison of mapping tools

Rahul Agarwal — Tue, 03 Sep 2013 18:00:38 -0500

A. Hatem, D. Bozdag, A. E. Toland, U. V. Catalyurek "Benchmarking short sequence mapping tools" BMC Bioinformatics, 14(1):184, 2013.

http://bmi.osu.edu/hpc/software/benchmark/

http://bmi.osu.edu/hpc/software/pmap/pmap.html

Other similiar papers:

http://online.liebertpub.com/doi/pdf/10.1089/cmb.2012.0022

http://bioinformatics.oxfordjournals.org/content/28/24/3169

Some new Mapping tool links:

GSNAP

http://research-pub.gene.com/gmap/

RMAP

http://rulai.cshl.edu/rmap/

mrsFAST

http://mrsfast.sourceforge.net/Home

http://sourceforge.net/projects/mrsfast/files/mrsfast-ultra-3.1.0/

BFAST

http://sourceforge.net/apps/mediawiki/bfast/index.php?title=Main_Page

SHRiMP (for AB SOLiD color-space reads)

http://compbio.cs.toronto.edu/shrimp/

RazerA 3

http://www.seqan.de/projects/razers/

Address of the bookmark: http://www.biomedcentral.com/1471-2105/14/184

Largest Genome Sequenced

Rahul Agarwal — Fri, 21 Mar 2014 13:57:19 -0500

The enormous size of the loblolly pine genome having 22 billion base pairs compared to only 3 billion in the human genome. In other words, it is seven times larger than a human’s and also the largest and the most complete conifer genome ever sequenced.

Related Paper:

http://genomebiology.com/2014/15/3/R59/abstract

Address of the bookmark: http://www.news.ucdavis.edu/search/news_detail.lasso?id=10859

New RNA Seq tool

Rahul Agarwal — Fri, 25 Apr 2014 10:59:04 -0500

"By removing the time-consuming step of read mapping, the authors reported, Sailfish able to provide quantification estimates 20–30 times faster than current methods without loss of accuracy."

Tool link:

http://www.cs.cmu.edu/~ckingsf/software/sailfish/

Address of the bookmark: http://www.genengnews.com/gen-news-highlights/lightweight-algorithms-sail-through-rna-sequencing-data/81249765/

GenXPro GmbH

Rahul Agarwal — Thu, 22 May 2014 07:18:35 -0500

GenXPro GMbH is service provider for entire spectrum of nucleotide-based information of any biological sample. By combining intelligent data reduction techniques and latest next generation sequencing technologies, our service portfolio provides most accurate and cost efficient solutions for transcriptomic-, genomic- or epigenomic research.

GENXPRO GMBH, ALTENHÖFERALLEE 3, 60438 FRANKFURT MAIN, GERMANY

Website: http://www.genxpro.info/products_and_services/

PHONE: +49 (0)69- 95 73 97 10, FAX: +49 (0)69- 95 73 97 06

EMAIL: info@genxpro.de

The Genome 10K Project

Tue, 29 Jul 2014 09:11:04 -0500

https://genome10k.soe.ucsc.edu The Genome 10K project aims to assemble a genomic zoo—a collection of DNA sequences representing the genomes of 10,000 vertebrate species, approximately one for every vertebrate genus. The trajectory of cost reduction in DNA sequencing suggests that this project will be feasible within a few years. Capturing the genetic diversity of vertebrate species would create an unprecedented resource for the life sciences and for worldwide conservation efforts. The growing Genome 10K Community of Scientists (G10KCOS), made up of leading scientists representing major zoos, museums, research centers, and universities around the world, is dedicated to coordinating efforts in tissue specimen collection that will lay the groundwork for a large-scale sequencing and analysis project.

GraphMap - A highly sensitive and accurate mapper for long, error-prone reads

Rahul Agarwal — Mon, 06 Jul 2015 08:46:53 -0500

GraphMap is a novel mapper targeted at aligning long, error-prone third-generation sequencing data.
It is designed to handle Oxford Nanopore MinION 1d and 2d reads with very high sensitivity and accuracy, and also presents a significant improvement over the state-of-the-art for PacBio read mappers.

GraphMap was also designed for ease-of-use: the default parameters can handle a wide range of read lengths and error profiles, including: Illumina, PacBio and Oxford Nanopore.
This is an especially important feature for technologies where the error rates and error profiles can vary widely across, or even within, sequencing runs.

http://biorxiv.org/content/early/2015/06/10/020719

Address of the bookmark: https://github.com/isovic/graphmap