<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/30002?offset=1180 https://bioinformaticsonline.com/bookmarks/view/37524/fmlrc-a-long-read-error-correction-tool-using-the-multi-string-burrows-wheeler-transform Fri, 10 Aug 2018 13:29:28 -0500 https://bioinformaticsonline.com/bookmarks/view/37524/fmlrc-a-long-read-error-correction-tool-using-the-multi-string-burrows-wheeler-transform <![CDATA[FMLRC: a long-read error correction tool using the multi-string Burrows Wheeler Transform]]> FMLRC, or FM-index Long Read Corrector, is a tool for performing hybrid correction of long read sequencing using the BWT and FM-index of short-read sequencing data. Given a BWT of the short-read sequencing data, FMLRC will build an FM-index and use that as an implicit de Bruijn graph. Each long read is then corrected independently by identifying low frequency k-mers in the long read and replacing them with the closest matching high frequency k-mers in the implicit de Bruijn graph. In contrast to other de Bruijn graph based implementations, FMLRC is not restricted to a particular k-mer size and instead uses a two pass method with both a short "k-mer" and a longer "K-mer". This allows FMLRC to correct through low complexity regions that are computational difficult for short k-mers.

Address of the bookmark: https://github.com/holtjma/fmlrc

]]> Neel https://bioinformaticsonline.com/bookmarks/view/11030/r-programming-and-jobs-website Sun, 25 May 2014 14:43:57 -0500 https://bioinformaticsonline.com/bookmarks/view/11030/r-programming-and-jobs-website <![CDATA[R programming and Jobs website]]> Welcome to the R Jobs section of ProgrammingR.com. If your organization has an R employment opportunity that you would like to have posted here, submit it via the contact page. Prospective employees: use the contact information provided in the position listing to apply or contact the hiring organization.

Address of the bookmark: http://www.programmingr.com/category/stype/r-job-listings/

]]> Pragati Singh https://bioinformaticsonline.com/bookmarks/view/37672/seqmonka-tool-to-visualise-and-analyse-high-throughput-mapped-sequence-data Tue, 11 Sep 2018 04:39:38 -0500 https://bioinformaticsonline.com/bookmarks/view/37672/seqmonka-tool-to-visualise-and-analyse-high-throughput-mapped-sequence-data <![CDATA[SeqMonk:A tool to visualise and analyse high throughput mapped sequence data]]> SeqMonk is a program to enable the visualisation and analysis of mapped sequence data. It was written for use with mapped next generation sequence data but can in theory be used for any dataset which can be expressed as a series of genomic positions. It's main features are:

  • Import of mapped data from mapped data (BAM/SAM/bowtie etc)
  • Creation of data groups for visualisation and analysis
  • Visualisation of mapped regions against an annotated genome.
  • Flexible quantitation of the mapped data to allow comparisons between data sets
  • Statistical analysis of data to find regions of interest
  • Creation of reports containing data and genome annotation

Address of the bookmark: http://www.bioinformatics.babraham.ac.uk/projects/seqmonk/

]]> Jit https://bioinformaticsonline.com/bookmarks/view/37837/clipcrop-a-tool-for-detecting-structural-variations-with-single-base-resolution-using-soft-clipping-information Thu, 04 Oct 2018 16:39:28 -0500 https://bioinformaticsonline.com/bookmarks/view/37837/clipcrop-a-tool-for-detecting-structural-variations-with-single-base-resolution-using-soft-clipping-information <![CDATA[ClipCrop: a tool for detecting structural variations with single-base resolution using soft-clipping information]]> This is a tool for detecting structural variations using soft-clipping information From SAM files.

https://github.com/shinout/clipcrop

Address of the bookmark: https://github.com/shinout/clipcrop

]]> Rahul Nayak https://bioinformaticsonline.com/videolist/watch/11311/stephen-friend-the-hunt-for-unexpected-genetic-heroes Sat, 31 May 2014 14:31:47 -0500 https://bioinformaticsonline.com/videolist/watch/11311/stephen-friend-the-hunt-for-unexpected-genetic-heroes <![CDATA[Stephen Friend: The hunt for "unexpected genetic heroes"]]> What can we learn from people with the genetics to get sick — who don't? With most inherited diseases, only some family members will develop the disease, while others who carry the same genetic risks dodge it. Stephen Friend suggests we start studying those family members who stay healthy. Hear about the Resilience Project, a massive effort to collect genetic materials that may help decode inherited disorders. TEDTalks is a daily video podcast of the best talks and performances from the TED Conference, where the world's leading thinkers and doers give the talk of their lives in 18 minutes (or less). Look for talks on Technology, Entertainment and Design -- plus science, business, global issues, the arts and much more. Find closed captions and translated subtitles in many languages at http://www.ted.com/translate Follow TED news on Twitter: http://www.twitter.com/tednews Like TED on Facebook: https://www.facebook.com/TED Subscribe to our channel: http://www.youtube.com/user/TEDtalksDirector]]> https://bioinformaticsonline.com/bookmarks/view/38561/hawkeye-an-interactive-visual-analytics-tool-for-genome-assemblies Tue, 01 Jan 2019 11:56:17 -0600 https://bioinformaticsonline.com/bookmarks/view/38561/hawkeye-an-interactive-visual-analytics-tool-for-genome-assemblies <![CDATA[Hawkeye: an interactive visual analytics tool for genome assemblies]]> Genome sequencing remains an inexact science, and genome sequences can contain significant errors if they are not carefully examined. Hawkeye is our new visual analytics tool for genome assemblies, designed to aid in identifying and correcting assembly errors. Users can analyze all levels of an assembly along with summary statistics and assembly metrics, and are guided by a ranking component towards likely mis-assemblies. Hawkeye is freely available and released as part of the open source AMOS project http://amos.sourceforge.net/hawkeye.

https://genomebiology.biomedcentral.com/articles/10.1186/gb-2007-8-3-r34

Address of the bookmark: http://amos.sourceforge.net/wiki/index.php?title=Hawkeye

]]> Abhimanyu Singh https://bioinformaticsonline.com/opportunity/view/12896/inspire-faculty-scheme-a-component-of-%E2%80%9Cassured-opportunity-for-research-career-aorc%E2%80%9D-under-inspire Sat, 19 Jul 2014 14:59:30 -0500 <![CDATA[INSPIRE Faculty Scheme: a component of “Assured Opportunity for Research Career (AORC)” under INSPIRE.]]> Ministry of Science and Technology, Department of Science and Technology

7th ADVERTISEMENT – 2014 (2)

INSPIRE Faculty Scheme: a component of “Assured Opportunity for Research Career (AORC)” under INSPIRE.

The Department of Science and Technology, Government of India, has launched the “Innovation in Science Pursuit for Inspired Research (INSPIRE)” [http://www.inspire-dst.gov.in] program in 2008.

The program aims to attract talent for study of science and careers with research. INSPIRE includes many components. The importance of Assured Career Opportunity in R&D sector has been recognized.

INSPIRE Faculty Scheme opens up an “Assured Opportunity for Research Career (AORC)” for young researchers in the age group of 27-32 years. It offers a contractual research awards to young achievers and opportunity for independent research in the near term and emerge as a future leader in the long term.

Eligibility

Essential Indian citizens and people of Indian origin including NRI/PIO status with PhD (in science, mathematics, engineering, pharmacy, medicine, and agriculture related subjects) from any recognized university in the world,

Those who have submitted their PhD Theses and are awaiting award of the degree are also
eligible. However, the award will be conveyed only after confirmation of the awarding the
PhD degree.

The upper age limit as on 1st July 2014 should be 32 years for considering support for a
period of 5 years. However, for SC and ST candidates, upper age limit will be 35 years.

Publication(s) in highly reputed Journals demonstrating research potential of the candidate.

Desirable

Candidates who are within top 1% at the School Leaving Examination, IIT-JEE rank, 1st Rank Holder either in graduation or post-graduation level university examination (which are used presently for identifying INSPIRE Scholars at under-graduate level and INSPIRE Fellows for doctoral degree)

More at http://www.inspire-dst.gov.in/faculty_scheme.html

]]> https://bioinformaticsonline.com/bookmarks/view/39728/patterns-a-modeling-tool-dedicated-to-biological-network-modeling Fri, 26 Jul 2019 01:11:59 -0500 https://bioinformaticsonline.com/bookmarks/view/39728/patterns-a-modeling-tool-dedicated-to-biological-network-modeling <![CDATA[Patterns: a modeling tool dedicated to biological network modeling]]> It is designed to work with patterned data. Famous examples of problems related to patterned data are:

  • recovering signals in networks after a stimulation (cascade network reverse engineering),
  • analysing periodic signals.

Address of the bookmark: https://github.com/fbertran/Patterns

]]> Abhimanyu Singh https://bioinformaticsonline.com/bookmarks/view/40721/efs-an-ensemble-feature-selection-tool-implemented-as-r-package-and-web-application Tue, 28 Jan 2020 05:12:23 -0600 https://bioinformaticsonline.com/bookmarks/view/40721/efs-an-ensemble-feature-selection-tool-implemented-as-r-package-and-web-application <![CDATA[EFS: an ensemble feature selection tool implemented as R-package and web-application]]> The software EFS (Ensemble Feature Selection) makes use of multiple feature selection methods and combines their normalized outputs to a quantitative ensemble importance. Currently, eight different feature selection methods have been integrated in EFS, which can be used separately or combined in an ensemble.

https://biodatamining.biomedcentral.com/articles/10.1186/s13040-017-0142-8

Address of the bookmark: http://efs.heiderlab.de/

]]> Jit https://bioinformaticsonline.com/news/view/11603/ncbi-webinar Sun, 08 Jun 2014 02:47:01 -0500 https://bioinformaticsonline.com/news/view/11603/ncbi-webinar <![CDATA[NCBI Webinar]]> In less than two weeks, NCBI will offer a webinar entitled "Introducing 3 NCBI Resources to Navigate Testing for Disease Linked Variants: MedGen, GTR and ClinVar". This webinar will delve into the lifecycle of genetic testing and teach attendees how to navigate the NIH Genetic Testing Registry, ClinVar, and MedGen resources. These resources can be used to prepare for clinical cases, access detailed information about orderable genetic tests, interpret test results, and more.

More at https://attendee.gotowebinar.com/register/8452228815737989634

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