<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/39867?offset=90 https://bioinformaticsonline.com/bookmarks/view/43815/kebabs-package-provides-functionality-for-kernel-based-analysis-of-biological-sequences-via-support-vector-machine-svm-based-methods Fri, 04 Mar 2022 00:14:11 -0600 https://bioinformaticsonline.com/bookmarks/view/43815/kebabs-package-provides-functionality-for-kernel-based-analysis-of-biological-sequences-via-support-vector-machine-svm-based-methods <![CDATA[kebabs: package provides functionality for kernel based analysis of biological sequences via Support Vector Machine (SVM) based methods]]> The kebabs package provides functionality for kernel based analysis of biological sequences via Support Vector Machine (SVM) based methods. Biological sequences include DNA, RNA, and amino acid (AA) sequences. Sequence kernels define similarity measures between sequences. The package implements some of the most important kernels for sequence analysis in a very flexible and efficient way and extends the standard position-independent functionality of these kernels in a novel way to take the position of patterns in the sequences into account for the similarity measure.

http://www.bioinf.jku.at/software/kebabs/

http://bioconductor.org/packages/release/bioc/vignettes/kebabs/inst/doc/kebabs.pdf

Address of the bookmark: http://www.bioinf.jku.at/software/kebabs/

]]> Rahul Nayak https://bioinformaticsonline.com/bookmarks/view/44479/doubletrouble-identify-duplicated-genes-from-whole-genome-protein-sequences-and-classify Tue, 05 Mar 2024 00:23:49 -0600 https://bioinformaticsonline.com/bookmarks/view/44479/doubletrouble-identify-duplicated-genes-from-whole-genome-protein-sequences-and-classify <![CDATA[doubletrouble: identify duplicated genes from whole-genome protein sequences and classify]]> doubletrouble aims to identify duplicated genes from whole-genome protein sequences and classify them based on their modes of duplication. The duplication modes are i. segmental duplication (SD); ii. tandem duplication (TD); iii. proximal duplication (PD); iv. transposed duplication (TRD) and; v. dispersed duplication (DD). Transposon-derived duplicates (TRD) can be further subdivided into rTRD (retrotransposon-derived duplication) and dTRD (DNA transposon-derived duplication). If users want a simpler classification scheme, duplicates can also be classified into SD- and SSD-derived (small-scale duplication) gene pairs. Besides classifying gene pairs, users can also classify genes, so that each gene is assigned a unique mode of duplication. Users can also calculate substitution rates per substitution site (i.e., Ka and Ks) from duplicate pairs, find peaks in Ks distributions with Gaussian Mixture Models (GMMs), and classify gene pairs into age groups based on Ks peaks.

Address of the bookmark: https://bioconductor.org/packages/release/bioc/html/doubletrouble.html

]]> LEGE https://bioinformaticsonline.com/bookmarks/view/44896/jaeger-an-accurate-and-fast-deep-learning-tool-to-detect-bacteriophage-sequences Sun, 31 Aug 2025 06:30:16 -0500 https://bioinformaticsonline.com/bookmarks/view/44896/jaeger-an-accurate-and-fast-deep-learning-tool-to-detect-bacteriophage-sequences <![CDATA[Jaeger : an accurate and fast deep-learning tool to detect bacteriophage sequences]]> Jaeger is a tool that utilizes homology-free machine learning to identify phage genome sequences that are hidden within metagenomes. It is capable of detecting both phages and prophages within metagenomic assemblies.

Address of the bookmark: https://github.com/MGXlab/Jaeger

]]> LEGE https://bioinformaticsonline.com/bookmarks/view/37416/gfinisher-a-new-strategy-to-refine-and-finish-bacterial-genome-assemblies Thu, 26 Jul 2018 09:31:55 -0500 https://bioinformaticsonline.com/bookmarks/view/37416/gfinisher-a-new-strategy-to-refine-and-finish-bacterial-genome-assemblies <![CDATA[GFinisher: a new strategy to refine and finish bacterial genome assemblies]]> GFinisher is an application tools for refinement and finalization of prokaryotic genomes assemblies using the bias of GC Skew to identify assembly errors and organizes the contigs/scaffolds with genomes references.

java -Xms2G -Xmx4G -jar GenomeFinisher.jar  \
    -i target_contigs.fasta  \
    -ds alternative_assemblies.fasta -ref reference.fasta  \
    -o outputDirectory

Address of the bookmark: http://gfinisher.sourceforge.net

]]> Jit https://bioinformaticsonline.com/bookmarks/view/36827/sex-detector-a-probabilistic-approach-to-study-sex-chromosomes-in-non-model-organisms Wed, 30 May 2018 15:57:31 -0500 https://bioinformaticsonline.com/bookmarks/view/36827/sex-detector-a-probabilistic-approach-to-study-sex-chromosomes-in-non-model-organisms <![CDATA[SEX-DETector: A Probabilistic Approach to Study Sex Chromosomes in Non-Model Organisms]]> SEX-DETector is a probabilistic method that relies on RNAseq data from a cross (parents and progeny of each sex) to infer autosomal and sex-linked genes (genes located on the non recombining part of sex chromosomes).

How does SEX-DETector work?

SEX-DETector does not require prior sequencing of a reference genome: the same sequencing data can be used for the assembly and for the mapping of the reads. A full documentation on the pipeline can be found here.

  • we recommend Trinity for the assembly.
  • Trinity components should be merged with cap3. Our code to perform the merging is available here.
  • We recommend BWA for mapping of the reads.
  • When the mapping has been perfomed, the individuals need to be genotyped; SEX-DETector takes files produced by Reads2snp (which is available for download on the PopPhyl website) as input.

Address of the bookmark: http://lbbe.univ-lyon1.fr/-SEX-DETector-.html?lang=eg

]]> Surabhi Chaudhary https://bioinformaticsonline.com/bookmarks/view/39281/humcfs-a-database-of-fragile-sites-in-human-chromosomes Sun, 21 Apr 2019 20:17:29 -0500 https://bioinformaticsonline.com/bookmarks/view/39281/humcfs-a-database-of-fragile-sites-in-human-chromosomes <![CDATA[HumCFS: a database of fragile sites in human chromosomes]]> Fragile sites are specific chromosomal region that exhibit an increased frequency of chromosdomal breakge when cells are exposed to replicative stress. Since from the discovery of chromosomal fragile sites/regions (CFS), several line of evidence suggests their involvement in human pathologies and they have been recognized as a preferential site for integration of exogenous oncogenic DNA viruses and hotspots for chromosomal re-arrangement. There is large gap in our knowledge of human CFS region as knowledge about CFS are unequally distributed in literature, which impose a problem in studying these region. In order to address these issues, we develop this platform HumCFS, which provides comprehensive information about experimentally identified CFS at a single source.

https://link.springer.com/epdf/10.1186/s12864-018-5330-5?author_access_token=ICASEpyMAQaxLlKw--fyCG_BpE1tBhCbnbw3BuzI2RMA57KLmXk5bZabRUiDQzRFHXd6hjm4kWSiLV3mU5XVMitqXUwFMSo4x5vbfty0EDQ9PW1sd1h923_TYXkvJ5niSwAyZ7BklJ0ujFAFhcKtjw%3D%3D

Address of the bookmark: https://webs.iiitd.edu.in/raghava/humcfs/

]]> Abhimanyu Singh https://bioinformaticsonline.com/videolist/watch/3925/genome-annotation Sun, 25 Aug 2013 10:53:01 -0500 https://bioinformaticsonline.com/videolist/watch/3925/genome-annotation <![CDATA[Genome Annotation]]> Dr. Rob Edwards describes some of the problems, challenges, and approches in genome annotation, with a particular emphasis on how the Fellowship for the Interpretation of Genomes (FIG) developed subsystems using the SEED database available at http://www.theseed.org/]]> https://bioinformaticsonline.com/bookmarks/view/32868/pollux-platform-independent-error-correction-of-single-and-mixed-genomes Fri, 19 May 2017 09:41:27 -0500 https://bioinformaticsonline.com/bookmarks/view/32868/pollux-platform-independent-error-correction-of-single-and-mixed-genomes <![CDATA[Pollux: platform independent error correction of single and mixed genomes]]> Pollux: General-purpose error corrector that corrects errors introduced by Illumina, Ion Torrent, and Roche 454 sequencing technologies and can be applied to single- or mixed-genome data. In addition to correcting substitution errors, we locate and correct insertion, deletion, and homopolymer errors while remaining sensitive to low coverage areas of sequencing projects. Using published data sets, we correct 94% of Illumina MiSeq errors, 88% of Ion Torrent PGM errors, 85% of Roche 454 GS Junior errors. Introduced errors are 20 to 70 times more rare than successfully corrected errors. Furthermore, we show that the quality of assemblies improves when reads are corrected by our software.

https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-014-0435-6

Address of the bookmark: https://github.com/emarinier/pollux

]]> Jit https://bioinformaticsonline.com/bookmarks/view/36597/gappadder-a-sensitive-approach-for-closing-gaps-on-draft-genomes-with-short-sequence-reads Mon, 14 May 2018 05:25:48 -0500 https://bioinformaticsonline.com/bookmarks/view/36597/gappadder-a-sensitive-approach-for-closing-gaps-on-draft-genomes-with-short-sequence-reads <![CDATA[GAPPadder: A Sensitive Approach for Closing Gaps on Draft Genomes with Short Sequence Reads]]> This software is provided ``as is” without warranty of any kind. In no event shall the author be held responsible for any damage resulting from the use of this software. The program package, including source codes, executables, and this documentation, is distributed free of charge. If you use this program in a publication, please cite the following reference:
Chong Chu, Xin Li, and Yufeng Wu. "GAPPadder: A Sensitive Approach for Closing Gaps on Draft Genomes with Short Sequence Reads." bioRxiv (2017): 125534.

Address of the bookmark: https://github.com/Reedwarbler/GAPPadder

]]> Jit https://bioinformaticsonline.com/bookmarks/view/44635/1000-genomes-chile-project Thu, 08 Aug 2024 01:24:13 -0500 https://bioinformaticsonline.com/bookmarks/view/44635/1000-genomes-chile-project <![CDATA[1000 Genomes Chile Project]]> Welcome to Chile Sequence to Chile: A Genomic Exploration Project for the Future Genomics, the science that deciphers the complexity of DNA, immerses us in the world of life at its most basic level. On this journey into the depths of genetic information, we find the 1000 Genomes Chile Project, an initiative that seeks to explore and understand the genetic wealth of our country.

Deciphering Life at the Molecular Level DNA sequencing is the key that opens the door to invaluable knowledge. By understanding the genes that make up Chilean species, we unravel the secrets of their evolution, their resistance and their adaptation to the environment. In a world where biodiversity faces constant threats, sequencing becomes crucial for the conservation and understanding of our natural heritage.

Involving Everyone: A Nationwide Effort The 1000 Genomes Chile Project is not just a task for scientists. It is a country-wide effort that seeks the participation of everyone: from citizens to the government to the private sector. We believe in the importance of sharing knowledge, involving society in the selection of species to sequence, in monitoring progress and in applying the results to preserve our environment.

Address of the bookmark: https://1000genomas.cl/

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