BOL: Related items

Greengenes database

Jit — Wed, 29 Jun 2016 10:03:31 -0500

The greengenes web application provides access to the 2011 version of the greengenes 16S rRNA gene sequence alignment for browsing, blasting, probing, and downloading. The data and tools presented by greengenes can assist the researcher in choosing phylogenetically specific probes, interpreting microarray results, and aligning/annotating novel sequences. If you are an ARB user, you can use greengenes to keep your own local database current.

Address of the bookmark: http://greengenes.lbl.gov/cgi-bin/nph-index.cgi

CGView - Circular Genome Viewer

Rahul Nayak — Wed, 20 Jun 2018 10:15:57 -0500

CGView is a Java package for generating high quality, zoomable maps of circular genomes. Its primary purpose is to serve as a component of sequence annotation pipelines, as a means of generating visual output suitable for the web. Feature information and rendering options are supplied to the program using an XML file, a tab delimited file, or an NCBI ptt file. CGView converts the input into a graphical map (PNG, JPG, or Scalable Vector Graphics format), complete with labels, a title, legends, and footnotes. In addition to the default full view map, the program can generate a series of hyperlinked maps showing expanded views. The linked maps can be explored using any web browser, allowing rapid genome browsing, and facilitating data sharing. The feature labels in maps can be hyperlinked to external resources, allowing CGView maps to be integrated with existing web site content or databases. For examples of the various output types, see the CGView gallery. http://wishart.biology.ualberta.ca/cgview/gallery.html http://stothard.afns.ualberta.ca/downloads/CCT/index.html https://www.gview.ca/wiki/GView/WebHome https://server.gview.ca/ http://stothard.afns.ualberta.ca/cgview_server/ Paper https://academic.oup.com/bib/advance-article/doi/10.1093/bib/bbx081/4037458

Address of the bookmark: http://wishart.biology.ualberta.ca/cgview/

Proksee

LEGE — Wed, 27 Mar 2024 11:11:54 -0500

Proksee is an expert system for genome assembly, annotation and visualization. To begin using Proksee, provide a complete genome sequence, sequencing reads or a CGView/Proksee map JSON file.

Please Cite the Following

Grant JR, Enns E, Marinier E, Mandal A, Herman EK, Chen C, Graham M, Van Domselaar G, and Stothard P

Proksee: in-depth characterization and visualization of bacterial genomes

Nucleic Acids Research, 2023, gkad326, https://doi.org/10.1093/nar/gkad326

Address of the bookmark: https://proksee.ca/

Zombies like bacteria!!!

Rahul Agarwal — Tue, 03 Sep 2013 08:44:15 -0500

Do you believe in Zombies stories … Hmm confused? Don’t worry there is a news for you. Scientists from the Integrated Ocean Drilling Program have announced the findings of the long-lived bacteria, reproducing only once every 10,000 years, which have been found in rocks 2.5km (1.5 miles) below the ocean floor that are as much as 100 million years old.

" the microbes exist in very low concentrations, of around 1,000 microbes in every tea spoon full of rock, compared with billions or trillions of bacteria that would typically be found in the same amount of soil at Earth's surface."

Reference:

http://www.bbc.co.uk/news/science-environment-23855436

CLARK: Fast, accurate and versatile sequence classification system

Jit — Sat, 15 Feb 2020 01:49:01 -0600

CLARK, a method based on a supervised sequence classification using discriminative k-mers. Considering two distinct specific classification problems (see the article for details), namely (1) the taxonomic classification of metagenomic reads to known bacterial genomes, and (2) the assignment of BAC clones and transcript to chromosome arms/centromeres (in the absence of a finished assembly for the reference genome), CLARK outperforms in classification speed and precision the best state-of-the-art methods.

http://clark.cs.ucr.edu/Spaced/

Address of the bookmark: http://clark.cs.ucr.edu/Spaced/

Postdoc position in protein annotation and machine learning - Paris, France

Sat, 04 Oct 2014 08:10:45 -0500

We are interested in finding an excellent postdoc with interests in protein functional annotation, machine learning and computer grids. The position is open for 3.5 years at the Université Pierre et Marie Curie, in the heart of Paris.

Research topic: Protein function annotation, multiple probabilistic models, domain architecture, machine learning, combinatorial optimization, computer grid.

This project is run on the Laboratoire de Biologie Computationnelle et Quantitative UMR7238 CNRS-UPMC – Analytical Genomics team, headed by A.Carbone. It is co-advised with Pierre-Henri Wuillemin, Laboratoire d’Informatique de Paris 6 – Equipe DECISION.

The postdoc will be payed under a contract of Ingénieur de Recherche lasting 3.5 years and it is available from September 1st, 2014.

Group Web Page: http://www.lcqb.upmc.fr/AnalGenom/home.html

Ref. E-Mail: Alessandra Carbone alessandra.carbone@lip6.fr

MMseqs2.0: ultra fast and sensitive protein search and clustering suite

Jit — Thu, 22 Mar 2018 10:40:51 -0500

MMseqs2 (Many-against-Many sequence searching) is a software suite to search and cluster huge protein 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.

The MMseqs2 user guide is available as Github Wiki or as PDF file (Thanks to pandoc!)

Please cite: Steinegger M and Soeding J. MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nature Biotechnology, doi: 10.1038/nbt.3988 (2017).

Address of the bookmark: https://github.com/soedinglab/MMseqs2

CHSMiner: a GUI tool to identify chromosomal homologous segments

Jit — Sat, 18 Nov 2017 16:55:49 -0600

Background

The identification of chromosomal homologous segments (CHS) within and between genomes is essential for comparative genomics. Various processes including insertion/deletion and inversion could cause the degeneration of CHSs.

Results

Here we present a Java software CHSMiner that detects CHSs based on shared gene content alone. It implements fast greedy search algorithm and rigorous statistical validation, and its friendly graphical interface allows interactive visualization of the results. We tested the software on both simulated and biological realistic data and compared its performance with similar existing software and data source.

Conclusion

CHSMiner is characterized by its integrated workflow, fast speed and convenient usage. It will be useful for both experimentalists and bioinformaticians interested in the structure and evolution of genomes.

https://github.com/zhenwang100/CHSMiner

Address of the bookmark: https://almob.biomedcentral.com/articles/10.1186/1748-7188-4-2

Katju Lab

Fri, 26 Feb 2016 03:25:32 -0600

TheLab seek to understand the genetic factors contributing to genomic variation and phenotypic diversity. To this end, we employ molecular and bioinformatic tools to study evolutionary processes at the level of populations, both experimental and natural, and genomes. Our research interests encompass a wide range of topics, including the evolution of organellar and nuclear genomes, gene duplication and the origin of novel function, and the fitness and phenotypic consequences of mutation in evolution. For details regards ongoing projects, please see the Research page.

http://katjulab.com/research.html

S-plot2: Rapid Visual and Statistical Analysis of Genomic Sequences

Abhimanyu Singh — Tue, 02 Oct 2018 17:57:27 -0500

S-plot2 creates an interactive, two-dimensional heatmap capturing the similarities and dissimilarities in nucleotide usage between genomic sequences (partial or complete). In S-plot2, whole eukaryotic chromosomes and smaller prokaryotic genomes can be efficiently compared. The tool includes functionality to extract, analyze, and automate BLAST queries of regions of interest within the heatmap. This facilitates the investigation of quickly evolving coding regions, novel coding regions, and laterally transferred elements.

Address of the bookmark: https://bitbucket.org/lkalesinskas/splot