<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/30557?offset=270 https://bioinformaticsonline.com/researchlabs/view/17501/nieduszynski-group Fri, 26 Sep 2014 19:35:06 -0500 <![CDATA[Nieduszynski Group]]> Complete, accurate replication of the genome is essential for life. All chromosomes in eukaryotic cells must be duplicated and then segregated to daughter cells to ensure genetic integrity and produce the large number of cells that make up a multicellular organism. We are using genetic, genomic and computational methods to understand how chromosome replication is regulated to ensure genome stability. By focusing on the basic biology that underpins cell growth and division we aim to provide new insights that may help our understanding of diseases such as cancer and congenital disorders.

More http://www.nieduszynski.org/index.php
http://www.path.ox.ac.uk/research/cell-biology-and-pathology/conrad-nieduszynski-group

]]> https://bioinformaticsonline.com/bookmarks/view/37737/rebaler-program-for-conducting-reference-based-assemblies-using-long-reads Tue, 18 Sep 2018 07:52:41 -0500 https://bioinformaticsonline.com/bookmarks/view/37737/rebaler-program-for-conducting-reference-based-assemblies-using-long-reads <![CDATA[Rebaler: program for conducting reference-based assemblies using long reads.]]> Rebaler is a program for conducting reference-based assemblies using long reads. It relies mainly on minimap2 for alignment and Racon for making consensus sequences.

I made Rebaler for bacterial genomes (specifically for the task of testing basecallers). It should in principle work for non-bacterial genomes as well, but I haven't tested it.

Address of the bookmark: https://github.com/rrwick/Rebaler

]]> Jit https://bioinformaticsonline.com/opportunity/view/17515/ngs-online-training Sat, 27 Sep 2014 07:42:29 -0500 <![CDATA[NGS Online Training]]> ArrayGen Technologies announces to provide online NGS training through out the globe. Now analyze your own NGS datasets from anywhere.For more information contact us at training@arraygen.com

Please visit our site at www.arraygen.com

]]> https://bioinformaticsonline.com/bookmarks/view/38299/deepbinner-a-signal-level-demultiplexer-for-oxford-nanopore-reads Tue, 27 Nov 2018 03:38:49 -0600 https://bioinformaticsonline.com/bookmarks/view/38299/deepbinner-a-signal-level-demultiplexer-for-oxford-nanopore-reads <![CDATA[Deepbinner: a signal-level demultiplexer for Oxford Nanopore reads]]> Deepbinner is a tool for demultiplexing barcoded Oxford Nanopore sequencing reads. It does this with a deep convolutional neural network classifier, using many of the architectural advances that have proven successful in image classification. Unlike other demultiplexers (e.g. Albacore and Porechop), Deepbinner identifies barcodes from the raw signal (a.k.a. squiggle) which gives it greater sensitivity and fewer unclassified reads.

  • Reasons to use Deepbinner:
    • To minimise the number of unclassified reads (use Deepbinner by itself).
    • To minimise the number of misclassified reads (use Deepbinner in conjunction with Albacore demultiplexing).
    • You plan on running signal-level downstream analyses, like Nanopolish. Deepbinner can demultiplex the fast5 fileswhich makes this easier.
  • Reasons to not use Deepbinner:
    • You only have basecalled reads not the raw fast5 files (which Deepbinner requires).
    • You have a small/slow computer. Deepbinner is more computationally intensive than Porechop.
    • You used a sequencing/barcoding kit other than the ones Deepbinner was trained on.

Address of the bookmark: https://github.com/rrwick/Deepbinner

]]> Neel https://bioinformaticsonline.com/opportunity/view/17751/jrf-in-bioinformatics-inmas-drdodelhi Wed, 01 Oct 2014 07:01:07 -0500 <![CDATA[JRF in Bioinformatics @ INMAS, DRDO,Delhi]]> Institute of Nuclear Medicine and Allied Sciences (INMAS), Delhi under the aegis of Defence Research and Development Organisation (DRDO), is engaged in research and developmental work in radiation sciences, Neuro-Computing and Medical Image Processing. INMAS is looking for meritorious young researchers for pursuing research in the frontier areas at INMAS. The Institute invites applications from young and meritorious Indian nationals who are creative, have passion and desire to pursue R&D in frontier areas. INMAS possesses ambience of a research cum academic institute coupled with an advanced R&D infrastructure in a mission mode. It provides the best infrastructure, motivation and personality development prospects for talented students, dreaming of unparalleled success in their professional endeavors. INMAS provides state of the art research facilities for undertaking pioneering research with defence applications.

JRF (Maximum Tenure‐ Five Years: 2yrs as JRF and 3yrs as SRF)
A first class Master’s Degree in Bioinformatics (likely 2 posts)
Around Rs 16,000/ Plus 30% HRA (as per rules of funding agency)

Applications are invited from candidates possessing the above qualifications. The upper age limit is as on the last date for receipt of application. (5 years relaxation to SC/ST candidates, 3 years to OBC candidates, and other entitled categories as per Govt rules). Actual No. of vacancies may vary.

Application form can be download from the website www.drdo.gov.in and E Mailed to inmashrd@gmail.com.
Last date to apply by email is 1700 hrs on 15 Oct 2014
Incomplete applications are liable to be rejected.
Confirmation will be sent to short-listed candidates through email only
Antecedents of selected candidates will be verified.
Written Test will be conducted from 0930-1030 hrs. Latecomers will not be considered.
Candidates will be required to produce certificates/testimonials in original at the time of interview.
It may please be noted that offer of Fellowship does not confer on fellows any right for absorption in DRDO.
Candidates should carry photocopy of Application form sent by email with them.
No TA/DA will be paid for attending interview & on joining.
Last date to apply by email is 1700 hrs on 15 Oct 2014

More at http://drdo.gov.in/drdo/English/jrf29092014.pdf
http://drdo.gov.in/drdo/English/index.jsp?pg=inmas29092014.jsp

]]> https://bioinformaticsonline.com/bookmarks/view/38892/wtdbg2-a-fuzzy-bruijn-graph-approach-to-long-noisy-reads-assembly Mon, 04 Feb 2019 04:53:47 -0600 https://bioinformaticsonline.com/bookmarks/view/38892/wtdbg2-a-fuzzy-bruijn-graph-approach-to-long-noisy-reads-assembly <![CDATA[wtdbg2: A fuzzy Bruijn graph approach to long noisy reads assembly]]> Wtdbg2 is a de novo sequence assembler for long noisy reads produced by PacBio or Oxford Nanopore Technologies (ONT). It assembles raw reads without error correction and then builds the consensus from intermediate assembly output. 

./wtdbg2 -x rs -g 4.6m -t 16 -i reads.fa.gz -fo prefix
./wtpoa-cns -t 16 -i prefix.ctg.lay.gz -fo prefix.ctg.fa

Address of the bookmark: https://github.com/ruanjue/wtdbg2

]]> BioStar https://bioinformaticsonline.com/opportunity/view/17966/internship-program-for-bioinformatics-biotechnology-professionals-no-of-vacancy-2 Wed, 08 Oct 2014 01:10:08 -0500 <![CDATA[Internship Program for Bioinformatics / Biotechnology Professionals (No. Of Vacancy: 2)]]> ArrayGen is offering an Internship Program for Post graduate Bioinformatics / Biotechnology students and professionals. ArrayGen Technologies provide an excellent opportunity to gain research experience and explore if a scientific career is right for you. Currently we offer positions to outstanding students interested in Next Generation Sequencing (NGS) data analysis. Applications are accepted throughout the year. Accepted students will be listed on web with their schedules. Accepted students can attend our future workshops and trainings freely at the specified venue.

]]> https://bioinformaticsonline.com/bookmarks/view/40701/fastgt-an-alignment-free-method-for-calling-common-snvs-directly-from-raw-sequencing-reads Tue, 28 Jan 2020 03:27:33 -0600 https://bioinformaticsonline.com/bookmarks/view/40701/fastgt-an-alignment-free-method-for-calling-common-snvs-directly-from-raw-sequencing-reads <![CDATA[FastGT: an alignment-free method for calling common SNVs directly from raw sequencing reads]]> FastGT is a program package for whole-genome genotyping of genome variants directly from raw sequencing reads. It is written in C and runs in Linux. FastGT uses a list of variant-specific k-mer pairs that are unique in human genome, counts the frequency of k-mers in sequencing data and predicts the genotype. All this takes less than 1 hour on average low-cost Linux server.

http://bioinfo.ut.ee/FastGT/

https://github.com/bioinfo-ut/GenomeTester4/

Address of the bookmark: http://bioinfo.ut.ee/FastGT/

]]> Jit https://bioinformaticsonline.com/videolist/watch/18381/how-far-can-bioinformatics-go-creating-organisms-used-for-testing Fri, 17 Oct 2014 02:08:16 -0500 https://bioinformaticsonline.com/videolist/watch/18381/how-far-can-bioinformatics-go-creating-organisms-used-for-testing <![CDATA[How far can bioinformatics go creating organisms used for testing?]]> "I think you can get very far on a technical level. The problem is that a human body is more complex than just one cell." ... "At some point we still need clinical tests on animals and humans before we use it for real treatment. But we will likely be able to remove 99 % of animal tests in the future." Erik Lindahl, Professor of Theoretical and Computational Biophysics at KTH Royal Institute of Technology is telling us about his work. From the episode "Science for life – mapping the building blocks of the human body". Watch the rest of the talk, and other talks at www.crosstalks.tv Crosstalks is an academic talkshow produced by KTH Royal Institute of Technology and Stockholm University.]]> https://bioinformaticsonline.com/bookmarks/view/40972/deepbinner-a-signal-level-demultiplexer-for-oxford-nanopore-reads Mon, 10 Feb 2020 02:45:53 -0600 https://bioinformaticsonline.com/bookmarks/view/40972/deepbinner-a-signal-level-demultiplexer-for-oxford-nanopore-reads <![CDATA[Deepbinner: a signal-level demultiplexer for Oxford Nanopore reads]]> Deepbinner is a tool for demultiplexing barcoded Oxford Nanopore sequencing reads. It does this with a deep convolutional neural network classifier, using many of the architectural advances that have proven successful in image classification. Unlike other demultiplexers (e.g. Albacore and Porechop), Deepbinner identifies barcodes from the raw signal (a.k.a. squiggle) which gives it greater sensitivity and fewer unclassified reads.

Address of the bookmark: https://github.com/rrwick/Deepbinner

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