GoJS offers many advanced features for user interactivity such as drag-and-drop, copy-and-paste, in-place text editing, tooltips, context menus, automatic layouts, templates, data binding and models, transactional state and undo management, palettes, overviews, event handlers, commands, and an extensible tool system for custom operations.

GoJS is pure JavaScript, so users get interactivity without requiring round-trips to servers and without plugins. GoJS normally runs completely in the browser, rendering to an HTML5 Canvas element or SVG without any server-side requirements. GoJS does not depend on any JavaScript libraries or frameworks, so it should work with any HTML or JavaScript framework or with no framework at all.          

More at http://gojs.net/latest/index.html

Address of the bookmark: http://gojs.net/latest/index.html

Address of the bookmark: https://sourceforge.net/projects/excavator2tool/

Advertisement for Faculty Positions

The IISER Berhampur, an Institute of national importance, established through an act of Parliament is an autonomous organization under the Ministry of HRD, Govt. of India, to promote quality education and cutting edge research in basic sciences and to provide a platform for the faculty to engage in high quality education, at undergraduate and postgraduate levels. The Institute invites applications for faculty positions at the level of Assistant Professor (C) /Assistant Professor in the following disciplines:

1. Biological Sciences

2. Chemistry

3. Computer Sciences

4. Mathematics

5. Physics

Only hard copy of application in the prescribed format, via Speed Post should be sent to the Dean, Faculty Affairs, IISER Berhampur, Industrial Training Institute (ITI) Berhampur, Engineering School Road, Berhampur - 760 010, Ganjam District, Odisha, before 1700 hrs., December 30, 2016.

http://www.iiserbpr.ac.in

More Info : http://www.iiserbpr.ac.in/vacancies/Advertisement%20for%20Faculty%20Positions%20at%20IISER%20Berhampur.pdf

The MEME Suite allows the biologist to discover novel motifs in collections of unaligned nucleotide or protein sequences, and to perform a wide variety of other motif-based analyses.

The MEME Suite supports motif-based analysis of DNA, RNA and protein sequences. It provides motif discovery algorithms using both probabilistic (MEME) and discrete models (MEME), which have complementary strengths. It also allows discovery of motifs with arbitrary insertions and deletions (GLAM2). In addition to motif discovery, the MEME Suite provides tools for scanning sequences for matches to motifs (FIMO, MAST and GLAM2Scan), scanning for clusters of motifs (MCAST), comparing motifs to known motifs (Tomtom), finding preferred spacings between motifs (SpaMo), predicting the biological roles of motifs (GOMo), measuring the positional enrichment of sequences for known motifs (CentriMo), and analyzing ChIP-seq and other large datasets (MEME-ChIP).

The MEME Suite is comprised of a collection of tools that work together, as shown below. Not all the tools are available as webservices, so to get the full power of the MEME Suite you will need to download and install a local copy of the software. To see what has changed recently you can peruse the release notes.

http://meme-suite.org/

Address of the bookmark: http://meme-suite.org/

• Speed: Prodigal is an extremely fast gene recognition tool (written in very vanilla C). It can analyze an entire microbial genome in 30 seconds or less.
• Accuracy: Prodigal is a highly accurate gene finder. It correctly locates the 3' end of every gene in the experimentally verified Ecogene data set (except those containing introns). It possesses a very sophisticated ribosomal binding site scoring system that enables it to locate the translation initiation site with great accuracy (96% of the 5' ends in the Ecogene data set are located correctly).
• Specificity: Prodigal's false positive rate compares favorably with other gene identification programs, and usually falls under 5%.
• GC-Content Indifferent: Prodigal performs well even in high GC genomes, with over a 90% perfect match (5'+3') to the Pseudomonas aeruginosa curated annotations.
• Metagenomic Version: Prodigal can run in metagenomic mode and analyze sequences even when the organism is unknown.
• Ease of Use: Prodigal can be run in one step on a single genomic sequence or on a draft genome containing many sequences. It does not need to be supplied with any knowledge of the organism, as it learns all the properties it needs to on its own.
• Open Source: Prodigal source code is freely available under the General Public License.

Address of the bookmark: http://prodigal.ornl.gov/

Availability: YAHA is currently supported on 64-bit Linux systems. Binaries and sample data are freely available for download from http://faculty.virginia.edu/irahall/YAHA.

Contact:

http://genome.wustl.edu/people/groups/detail/hall-lab/

Address of the bookmark: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3463118/

Applicant are required to bring applications on plain paper, stating the name, address, date of birth. educational qualifications and experiences and Institute, along with attested photocopies of mark sheets and certificates etc. at the time of Interview. Applications should also be sent by Entail to Dr. Madhu Chopra, Coordinator, BIF Facility. Email: acbrdu.blisnet@nic.in; mchopradu@gmail.com.
Interview Date : 13.02.2017
Time : 10:00 am-12:00 noon
Venue : ACBR

CORE MODULES

Three modules make up the core engine for MCE.

MCE::Core

Provides the Core API for Many-Core Engine. The various MCE options are described here.

MCE::Signal

Temporary directory creation, cleanup, and signal handling.

MCE::Util

Utility functions for Many-Core Engine.

MCE EXTRAS

There are 4 add-on modules for use with MCE.

MCE::Candy

Provides a collection of sugar methods and output iterators for preserving output order.

MCE::Mutex

Provides a simple semaphore implementation supporting threads and processes.

MCE::Queue

Provides a hybrid queuing implementation for MCE supporting normal queues and priority queues from a single module. MCE::Queue exchanges data via the core engine to enable queuing to work for both children (spawned from fork) and threads.

MCE::Relay

Enables workers to receive and pass on information orderly with zero involvement by the manager process while running.

MCE MODELS

The models take Many-Core Engine to a new level for ease of use. Two options (chunk_size and max_workers) are configured automatically as well as spawning and shutdown.

MCE::Loop

Provides a parallel loop utilizing MCE for building creative loops.

MCE::Flow

A parallel flow model for building creative applications. This makes use of user_tasks in MCE. The author has full control when utilizing this model. MCE::Flow is similar to MCE::Loop, but allows for multiple code blocks to run in parallel with a slight change to syntax.

MCE::Grep

Provides a parallel grep implementation similar to the native grep function.

MCE::Map

Provides a parallel map model similar to the native map function.

MCE::Step

Provides a parallel step implementation utilizing MCE::Queue between user tasks. MCE::Step is a spin off from MCE::Flow with a touch of MCE::Stream. This model, introduced in 1.506, allows one to pass data from one sub-task into the next transparently.

MCE::Stream

Provides an efficient parallel implementation for chaining multiple maps and greps together through user_tasks and MCE::Queue. Like with MCE::Flow, MCE::Stream can run multiple code blocks in parallel with a slight change to syntax from MCE::Map and MCE::Grep.

MISCELLANEOUS

Miscellaneous additions included with the distribution.

MCE::Examples

Describes various demonstrations for MCE including a Monte Carlo simulation.

MCE::Subs

Exports functions mapped directly to MCE methods; e.g. mce_wid. The module allows 3 options; :manager, :worker, and :getter.

REQUIREMENTS

Perl 5.8.0 or later. PDL::IO::Storable is required in scripts running PDL.

SOURCE AND FURTHER READING

The source, cookbook, and examples are hosted at GitHub.

• https://github.com/marioroy/mce-perl

• https://github.com/marioroy/mce-cookbook

• https://github.com/marioroy/mce-examples

SEE ALSO

MCE::Shared provides data sharing capabilities for MCE. It includes MCE::Hobo for running code asynchronously.

• MCE::Shared

• MCE::Hobo

Address of the bookmark: https://github.com/marioroy/mce-examples

Upcoming Deadlines
Regular Paper Submission: July 31, 2017
Regular Paper Authors Notification: October 16, 2017
Regular Paper Camera Ready and Registration: October 30, 2017

The purpose of the International Conference on Bioinformatics Models, Methods and Algorithms is to bring together researchers and practitioners interested in the application of computational systems, algorithmic concepts and information technologies to address challenging problems in Biomedical research with a particular focus on the emerging problems in Bioinformatics and computational biology. There is a tremendous need to explore how mathematical, statistical and computational models can be used to better understand biological processes and systems, while developing new methodologies and tools to analysis the massive currently-available biological data. Areas of interest to this community include systems biology, sequence analysis, biostatistics, image analysis, network and graph models, scientific data management and data mining, machine learning, pattern recognition, computational evolutionary biology, computational genomics and proteomics, and related areas.