<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/36755?offset=310 https://bioinformaticsonline.com/bookmarks/view/37584/mulan-multiple-sequence-local-alignment-and-visualization-for-studying-function-and-evolution Fri, 24 Aug 2018 09:50:01 -0500 https://bioinformaticsonline.com/bookmarks/view/37584/mulan-multiple-sequence-local-alignment-and-visualization-for-studying-function-and-evolution <![CDATA[Mulan: Multiple-sequence local alignment and visualization for studying function and evolution]]> Mulan: Multiple-sequence local alignment and visualization for studying function and evolution

Mulan (http://mulan.dcode.org/), a novel method and a network server for comparing multiple draft and finished-quality sequences to identify functional elements conserved over evolutionary time. Mulan brings together several novel algorithms: the TBA multi-aligner program for rapid identification of local sequence conservation, and the multiTF program for detecting evolutionarily conserved transcription factor binding sites in multiple alignments. In addition, Mulan supports two-way communication with the GALA database; alignments of multiple species dynamically generated in GALA can be viewed in Mulan, and conserved transcription factor binding sites identified with Mulan/multiTF can be integrated and overlaid with extensive genome annotation data using GALA.

Address of the bookmark: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC540288/

]]> Jit https://bioinformaticsonline.com/bookmarks/view/39837/cactus-a-reference-free-whole-genome-multiple-alignment-program Mon, 12 Aug 2019 07:52:33 -0500 https://bioinformaticsonline.com/bookmarks/view/39837/cactus-a-reference-free-whole-genome-multiple-alignment-program <![CDATA[Cactus: a reference-free whole-genome multiple alignment program]]> Cactus is a reference-free whole-genome multiple alignment program. The principal algorithms are described here: https://doi.org/10.1101/gr.123356.111

Cactus uses substantial resources. For primate-sized genomes (3 gigabases each), you should expect Cactus to use approximately 120 CPU-days of compute per genome, with about 120 GB of RAM used at peak. The requirements scale roughly quadratically, so aligning two 1-megabase bacterial genomes takes only 1.5 CPU-hours and 14 GB RAM. 

Address of the bookmark: https://github.com/ComparativeGenomicsToolkit/cactus

]]> Jit https://bioinformaticsonline.com/bookmarks/view/41910/the-wavefront-alignment-wfa-algorithm Sun, 28 Jun 2020 10:17:50 -0500 https://bioinformaticsonline.com/bookmarks/view/41910/the-wavefront-alignment-wfa-algorithm <![CDATA[The wavefront alignment (WFA) algorithm]]> The wavefront alignment (WFA) algorithm is an exact gap-affine algorithm that takes advantage of
homologous regions between the sequences to accelerate the alignment process. As opposed to traditional dynamic programming algorithms that run in quadratic time, the WFA runs in time O(ns), proportional to the read length n and the alignment score s, using O(s^2) memory. Moreover, the WFA exhibits simple data dependencies that can be easily vectorized, even by the automatic features of modern compilers, for different architectures, without the need to adapt the code.

Address of the bookmark: https://github.com/smarco/WFA

]]> BioStar https://bioinformaticsonline.com/bookmarks/view/37937/frodock-20-fast-protein%E2%80%93protein-docking-server Wed, 17 Oct 2018 04:31:30 -0500 https://bioinformaticsonline.com/bookmarks/view/37937/frodock-20-fast-protein%E2%80%93protein-docking-server <![CDATA[FRODOCK 2.0: fast protein–protein docking server]]> frodock: a user-friendly protein–protein docking server based on an improved version of FRODOCK that includes a complementary knowledge-based potential. The web interface provides a very effective tool to explore and select protein–protein models and interactively screen them against experimental distance constraints. The competitive success rates and efficiency achieved allow the retrieval of reliable potential protein–protein binding conformations that can be further refined with more computationally demanding strategies.

Address of the bookmark: http://frodock.chaconlab.org/

]]> Neel https://bioinformaticsonline.com/bookmarks/view/40389/sequila-cov-a-fast-and-scalable-library-for-depth-of-coverage-calculations Sun, 15 Dec 2019 10:19:35 -0600 https://bioinformaticsonline.com/bookmarks/view/40389/sequila-cov-a-fast-and-scalable-library-for-depth-of-coverage-calculations <![CDATA[SeQuiLa-cov: A fast and scalable library for depth of coverage calculations]]> The Docker image is available at https://hub.docker.com/r/biodatageeks/. Supplementary information on benchmarking procedure as well as test data are publicly accessible at the project documentation site http://biodatageeks.org/sequila/benchmarking/benchmarking.html#depth-of-coverage. An archival copy of the code and supporting data is also available via the GigaScience database GigaDB

• Project name: SeQuiLa-cov

• Project home page: http://biodatageeks.org/sequila/

• Source code repository: https://github.com/ZSI-Bio/bdg-sequila

• Operating system: Platform independent

• Programming language: Scala

• Other requirements: Docker

• License: Apache License 2.0

Address of the bookmark: https://academic.oup.com/gigascience/article/8/8/giz094/5543653

]]> 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/44904/termal-a-fast-and-interactive-terminal-based-viewer-for-multiple-sequence-alignments Mon, 22 Sep 2025 23:51:02 -0500 https://bioinformaticsonline.com/bookmarks/view/44904/termal-a-fast-and-interactive-terminal-based-viewer-for-multiple-sequence-alignments <![CDATA[Termal: a fast and interactive terminal-based viewer for multiple sequence alignments]]> termal, a fast, interactive, terminal-based viewer for multiple sequence alignments (MSAs), designed for use on remote systems such as high-performance computing (HPC) clusters.

https://academic.oup.com/bioinformaticsadvances/advance-article/doi/10.1093/bioadv/vbaf208/8257678?login=true

Address of the bookmark: https://github.com/sib-swiss/termal

]]> LEGE https://bioinformaticsonline.com/bookmarks/view/38012/cosine-non-seeding-method-for-mapping-long-noisy-sequences Fri, 26 Oct 2018 00:41:59 -0500 https://bioinformaticsonline.com/bookmarks/view/38012/cosine-non-seeding-method-for-mapping-long-noisy-sequences <![CDATA[COSINE: non-seeding method for mapping long noisy sequences]]> Third generation sequencing (TGS) are highly promising technologies but the long and noisy reads from TGS are difficult to align using existing algorithms. Here, we present COSINE, a conceptually new method designed specifically for aligning long reads contaminated by a high level of errors.

Address of the bookmark: https://github.com/SUwonglab/COSINE

]]> Jit https://bioinformaticsonline.com/bookmarks/view/35057/ectools-long-read-correction-and-other-correction-tools Fri, 05 Jan 2018 04:02:22 -0600 https://bioinformaticsonline.com/bookmarks/view/35057/ectools-long-read-correction-and-other-correction-tools <![CDATA[ECTOOLS: Long Read Correction and other Correction tools]]> Long Read Correction and other Correction tools

This package is a loose collection of scripts. To run the correction
routine see the section below. Descriptions of the other scripts
are at the bottom of this file.

Contact: gurtowsk@cshl.edu

In short, the correction algorithm takes as input the unitigs from a short read assembly and uses them to correct long read data. More background information for the algorithm can be found:
http://schatzlab.cshl.edu/presentations/2013-06-18.PBUserMeeting.pdf

Address of the bookmark: https://github.com/jgurtowski/ectools

]]> Jit https://bioinformaticsonline.com/poll/view/23590/will-minion-nanopore-sequencing-increase-the-number-of-next-generation-sequencing-projects Tue, 04 Aug 2015 05:14:07 -0500 https://bioinformaticsonline.com/poll/view/23590/will-minion-nanopore-sequencing-increase-the-number-of-next-generation-sequencing-projects <![CDATA[Will MinION Nanopore sequencing increase the number of Next Generation Sequencing projects?]]> Will MinION Nanopore sequencing increase the number of Next Generation Sequencing projects?

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