NGenomeSyn [multiple (N) Genome Synteny], for publication-ready visualization of syntenic relationships of the whole genome or local region and genomic features (e.g. repeats, structural variations, genes) across multiple genomes with a high customization. NGenomeSyn provides an easy way for its users to visualize a large amount of data with a rich layout by simply adjusting options for moving, scaling, and rotation of target genomes. Moreover, NGenomeSyn could be applied on the visualization of relationships on non-genomic data with similar input formats.

https://academic.oup.com/bioinformatics/article/39/3/btad121/7072460

Address of the bookmark: https://github.com/hewm2008/NGenomeSyn

Local installation:

You can install Ribbon locally from Github by following the instructions here: https://github.com/MariaNattestad/Ribbon

Address of the bookmark: http://genomeribbon.com/

Features

• An amazing real-time web framework, allowing you to easily grow single file prototypes into well-structured MVC web applications.
  • Powerful out of the box with RESTful routes, plugins, commands, Perl-ish templates, content negotiation, session management, form validation, testing framework, static file server, CGI/PSGI detection, first class Unicode support and much more for you to discover.
• A powerful web development toolkit, that you can use for all kinds of applications, independently of the web framework.
  • Full stack HTTP and WebSocket client/server implementation with IPv6, TLS, SNI, IDNA, HTTP/SOCKS5 proxy, UNIX domain socket, Comet (long polling), Promises/A+, keep-alive, connection pooling, timeout, cookie, multipart and gzip compression support.
  • Built-in non-blocking I/O web server, supporting multiple event loops as well as optional pre-forking and hot deployment, perfect for building highly scalable web services.
  • JSON and HTML/XML parser with CSS selector support.
• Very clean, portable and object-oriented pure-Perl API with no hidden magic and no requirements besides Perl 5.24.0 (versions as old as 5.10.1 can be used too, but may require additional CPAN modules to be installed)
• Fresh code based upon years of experience developing Catalyst, free and open source.
• Hundreds of 3rd party extensions and high quality spin-off projects like the Minion job queue.

http://mojolicious.org/

Address of the bookmark: http://mojolicious.org/

Address of the bookmark: http://busca.biocomp.unibo.it/

More at http://bmbl.sdstate.edu/DMINDA2/

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4086085/

Address of the bookmark: http://bmbl.sdstate.edu/DMINDA2/

Pst. hey, you, join our stargazers :)

Address of the bookmark: https://github.com/firecrawl/firecrawl

Address of the bookmark: https://saliweb.readthedocs.io/en/latest/frontend.html

Job Description: 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.

Title: A novel integrative platform for large scale protein annotation that exploits a multitude of diversified probabilistic models in several protein signature databases.

We propose a novel integrated approach for large scale protein annotation that will exploit an unprecedented amount of genomic data as well as sophisticated machine learning techniques and combinatorial optimization approaches taking advantages of High Performance Computing (HPC) environments. The idea is to uncover as much as possible the evolutionary processes of protein sequences that took place throughout the whole tree of life and that affected the evolution of a protein family. We have already demonstrated in a previous work that the problem of functional annotation is inherent to the ability of uncovering such paths. Now, we shall extend this approach to large scale genome annotation by considering 11 different protein databases, constituted by about 10^9 protein sequences, and by producing a large pool of diversified probabilistic models coding for about 10^7 evolutionary protein pathways. Such models will be used to search for specific domains in genomes to be annotated. Our previous methodology needs to be fundamentally improved to deal with this large amount of biological data. In this project, we shall work on the algorithms to reduce the space of models and the search complexity, and we shall implement some important algorithmic changes towards the realization of a powerful integrated annotation tool.

Where: 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.

Start date: September 1st, 2014
Contact Person: Alessandra Carbone
Contact: alessandra.carbone@lip6.fr

Lift over is the process of transferring annotations from one genome assembly to another. Usually lift over is done because there is a new, improved genome assembly for the species and good quality annotations (maybe manually curated or experimentally verified) are available on the old assembly.

The idea is simple: align the new assembly with the old one (e.g., with BLAT), process the alignment data to define how a coordinate or coordinate range on the old assembly should be transformed to the new assembly (e.g., as a chain file), transform the coordinates (e.g., with liftOver).

https://github.com/wurmlab/flo

Address of the bookmark: https://github.com/wurmlab/flo