BOL: Related items

Many-to-many pairwise alignments of two sequence sets

Poonam Mahapatra — Tue, 19 Jun 2018 08:34:15 -0500

needleall reads a set of input sequences and compares them all to one or more sequences, writing their optimal global sequence alignments to file. It uses the Needleman-Wunsch alignment algorithm to find the optimum alignment (including gaps) of two sequences along their entire length. The algorithm uses a dynamic programming method to ensure the alignment is optimum, by exploring all possible alignments and choosing the best. A scoring matrix is read that contains values for every possible residue or nucleotide match. Needleall finds the alignment with the maximum possible score where the score of an alignment is equal to the sum of the matches taken from the scoring matrix, minus penalties arising from opening and extending gaps in the aligned sequences. The substitution matrix and gap opening and extension penalties are user-specified.

Address of the bookmark: http://emboss.sourceforge.net/apps/release/6.6/emboss/apps/needleall.html

iRNAD: a computational tool for identifying D modification sites in RNA sequence

Abhimanyu Singh — Thu, 16 May 2019 00:20:07 -0500

iRNAD, for identifying D modification sites in RNA sequence. In this predictor, the RNA samples derived from five species were encoded by nucleotide chemical property and nucleotide density. Support vector machine was utilized to perform the classification.

http://lin-group.cn/server/iRNAD/

Address of the bookmark: http://lin-group.cn/server/iRNAD/

Apollo: a sequence annotation editor

Abhimanyu Singh — Tue, 27 Aug 2019 08:08:47 -0500

The well-established inaccuracy of purely computational methods for annotating genome sequences necessitates an interactive tool to allow biological experts to refine these approximations by viewing and independently evaluating the data supporting each annotation. Apollo was developed to meet this need, enabling curators to inspect genome annotations closely and edit them

Address of the bookmark: https://genomebiology.biomedcentral.com/articles/10.1186/gb-2002-3-12-research0082

GfaViz: flexible and interactive visualization of GFA sequence graphs

Jit — Thu, 23 Jan 2020 07:33:46 -0600

GFA (Graphical Fragment Assembly) is an emerging standard format for representing sequence graphs. Although it was originally conceived as a format for sequence assembly (hence the name), and this remains its core application, it is more general, and able to represent many different types of sequence graphs, including scaffolding graphs, alignment graphs, variant graphs and splicing graphs.

Address of the bookmark: https://github.com/ggonnella/gfaviz

Submit your SARS-CoV-2 sequence data to GenBank

Neel — Thu, 09 Apr 2020 18:28:25 -0500

Submit your SARS-CoV-2 sequence data to GenBank and SRA with our new submission landing page. Submission is simple and streamlined *and* there’s a rapid turnaround. https://submit.ncbi.nlm.nih.gov/sarscov2/

Quickly and easily add your SARS-CoV-2 sequence data to the growing public archive with new, special features and support from NCBI. new SARS-CoV-2 sequence submission landing page will help you get started. GenBank submissions are accessioned and released in approximately 1-2 working days, and Sequence Read Archive (SRA) submissions typically processed and released within hours. Submission is simple!

More information is available on NCBI Insights. https://ncbiinsights.ncbi.nlm.nih.gov/2020/04/09/sars-cov2-data-streamlined-submission-rapid-turnaround/

MMseqs2: ultra fast and sensitive sequence search and clustering suite

Manisha Mishra — Mon, 18 Jan 2021 10:47:56 -0600

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

ContigExtender: a new approach to improving de novo sequence assembly for viral metagenomics data

LEGE — Wed, 08 May 2024 07:32:45 -0500

ContigExtender, was developed to extend contigs, complementing de novo assembly. ContigExtender employs a novel recursive Overlap Layout Candidates (r-OLC) strategy that explores multiple extending paths to achieve longer and highly accurate contigs. ContigExtender is effective for extending contigs significantly in in silico synthesized and real metagenomics datasets.

More at https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7953547/

Address of the bookmark: https://github.com/dengzac/contig-extender

Seal: SEquence ALignment evaluation suite

Jit — Wed, 03 Jan 2018 05:05:46 -0600

Seal is a comprehensive sequencing simulation and alignment tool evaluation suite. This software (implemented in Java) provides several utilities that can be used to evaluate alignment algorithms, including:

Reading a pre-existing reference genome from one or more FASTA files.
Alternatively, generating an artificial reference genome based on input parameters (length, repeat count, repeat length, repeat variability rate).
Simulating reads from random locations in the genome based on input parameters of read length, coverage, sequencing error rate, and indel rate.
Applying alignment tools to the genome and the reads through a standardized interface.
Parsing the output of the alignment tool and calculating the number of reads that were correctly or incorrectly mapped.
Computing run times and measures of accuracy.

Seal has interfaces to evaluate the following software packages:

Bowtie
BWA
MAQ
mrFAST
mrsFAST
Novoalign
SHRiMP
SOAPv2

Address of the bookmark: http://compbio.case.edu/seal/

China University of Macau PhD Position 2015 in Bioinformatics, Computer Science

Mon, 22 Dec 2014 00:12:49 -0600

The Computational Biology and Bioinformatics Group at the University of Macau is inviting applications for PhD Position. Applicants will work on a research project focusing on the flexible receptor protein-ligand docking algorithms for computer-aided drug design. The candidate will be working as part of a team in developing novel metaheuristic algorithms and scoring functions for large-scale, highly flexible protein-ligand docking problems. The duration of this PhD position is 2-3 years, starting in August 2015. Remuneration paid to candidate is MOP 11000-14000/month (~USD 1375-1750/month). The applications should be submitted before March 2015.

Study Subject(s): PhD position is award in the field of Bioinformatics/Computer Science.
Course Level: Position is available for pursuing PhD degree level at the University of Macau.
Scholarship Provider: University of Macau
Scholarship can be taken at: China

Eligibility: The ideal candidate would be a master degree holder in Bioinformatics or related disciplines with knowledge in Medical sciences or Life sciences (with GPA of at least 3.0 on a 4-point scale or equivalent) . Knowledge in programming (C and C++) and Linux scripting are necessary; experience in molecular docking, molecular dynamics simulations or molecular modeling is an advantage. The candidate should be fluent in spoken and written English; preference will be given to applicants with good publication records in relevant areas.

Scholarship Open for International Students: Researchers from China can apply for this PhD position.

Scholarship Description:

The Computational Biology and Bioinformatics Group at the University of Macau is looking for a motivated PhD student in Bioinformatics or Computer Science to work on a research project focusing on the flexible receptor protein-ligand docking algorithms for computer-aided drug design. The candidate will be working as part of a team in developing novel metaheuristic algorithms and scoring functions for large-scale, highly flexible protein-ligand docking problems.

Number of award(s): There is only one PhD position available.

Duration of award(s): The duration of this PhD position is 2-3 years.

What does it cover? Remuneration paid to candidate is MOP 11000-14000/month (~USD 1375-1750/month).

Selection Criteria: Not Known

Notification: Not Known

How to Apply: Send your current CV, your academic transcripts, a letter of motivation and research interests, two letters of recommendations from academic faculty to Dr. Shirley Siu at shirleysiu[at]umac.mo before March 2015.

Scholarship Application Deadline: The applications should be submitted before March 2015.

NGS Platforms launched by BGI’s MGI Tech

Jit — Thu, 10 Jan 2019 04:42:06 -0600

MGI Tech Co., Ltd. (MGI), a subsidiary of BGI Group, is committed to enabling effective and affordable healthcare solutions for all. Based on its proprietary technology, MGI produces sequencing devices, equipment, consumables and reagents to support life science research, medicine and healthcare. MGI's multi-omics platforms include genetic sequencing, mass spectrometry and medical imaging. Providing real-time, comprehensive, life-long solutions, its mission is to develop and promote advanced life science tools for future healthcare.

MGI, a subsidiary of global genomics leader BGI Group, announced pricing and its first early access customer for the new ultra high-throughput sequencer, MGISEQ-T7, saying it has driven down sequencing cost to $5 per gigabyte, with exceptionally high accuracy. Such innovations are helping more people to realize the benefits of genomic information.

In October, MGI launched the MGISEQ-T7, a highly flexible production-scale platform that is the most powerful sequencer to date. It can produce as many as 60 whole human genomes in one day. The instrument sells for $1 million.

The T7 enables simultaneous but independent operation of up to four flow cells, which means different applications such as single-cell RNA sequencing, whole exome sequencing and whole genome sequencing can be run in different flow cells at the same time. This helps to reduce costs, allowing MGI to offer the most competitive sequencing price in the market.

Powered by DNBseq™, MGISEQ delivers quality data with accuracy for SNP and Indel calling rate of 99.9% and 99%, respectively, along with decreased duplication rate down to less than 2 percent, and almost zero Index mis-assignment rate.

SOURCE MGI

https://www.bgi.com/global/company/news/bgis-mgi-tech-launches-two-new-ngs-platforms/

http://en.mgitech.cn/