BOL: Related items

WEGO : simple but useful tool for visualizing, comparing and plotting GO (Gene Ontology) annotation results

BioStar — Sun, 12 Apr 2020 10:02:22 -0500

WEGO (Web Gene Ontology Annotation Plot) is a simple but useful tool for visualizing, comparing and plotting GO (Gene Ontology) annotation results. As the GO vocabulary became more and more popular, WEGO was widely adopted and used in many researches. Therefore we have updated WEGO 2.0 in 2018. Here are some changes we’ve made:
1. The limit of input file numbers was cancelled. Now the users could upload as many files as they want with one operation.
2. We have added the reference data of 9 species for users selection.
3. Besides the traditional WEGO histogram, WEGO 2.0 outputs an additional type of bar graph showing GO terms with significant gene number differences.

Address of the bookmark: http://wego.genomics.org.cn/

SCFBio have developed Sanjeevini

Jit — Fri, 17 Nov 2017 07:55:49 -0600

SCFBio have developed a new android based application for drug design called Sanjeevini (https://play.google.com/store/apps/details?id=com.sanjeevini&hl=en). It is available free of charge. You can download it using Google play store. Just search for "Sanjeevini-SCFBIO-CADD" in Google play store. It contains all modules used by current Sanjeevini users. We have worked towards making a unified and easy to use interface. The app now supports all major small molecule file formats (pdb, mol, sdf, mol2 and xyz). The application contains inbuilt visualizer JSmol for easy analysis of results. Users can now directly download the protein files from PDB ("Get protein PDB file" in `FILE` Menu) and prepare it using the easy to use in-built module "Prepare protein/DNA".

SCFBio have worked towards making the process of Job retrieval more streamlined and user friendly. All jobs are now recorded in the "Job results". It can be accessed using the main page of the application. Job status can now be retrieved by clicking on the refresh button against the job ID.

SCFBio have also added a new feature of accessing Jobs run on different android application. Users can retrieve jobs run by other users by sharing the job ID and module name. This feature can be accessed using the Import Jobs option in File menu. We hope this feature will help collaborating groups stay in touch with each other.

The module contains all modules of Sanjeevini suite of software for structure based Drug design.

Sl No.	Module name	Activity
1	Prepare Protein/DNA	Prepares protein/DNA for other modules of Sanjeevini
2	Prepare ligand	Prepares ligands for other modules of Sanjeevini
3	Active site Prediction	Predicts biologically relevant sites in a protein
4	ParDOCK	Rigid Docking of Protein-Ligand complex
5	BAPPL	Binding affinity prediction of Protein-Ligand complex
6	BAPPL Z	Binding affinity prediction of Protein-Zinc-Ligand complex
7	DNA ligand Docking	Rigid Docking of DNA-Ligand complex
8	PreDDICTA	Binding affinity prediction of DNA-Ligand complex
9	SOM Prediction	Rigid Docking of Ligand and CYP proteins
10	Lipinski filters	Checks Lipinski's rule of five for ligand molecule
11	Molecular volume	Calculates volume of a ligand
12	RASPD	Virtual screening of protein molecule to yield hit molecules
13	AADS	Prediction and docking of top 10 biologically relevant sites on protein
14	Intercalate	Rigid Docking of DNA-Ligand complex in intercalation sites
15	DNA sequence to str.	Converts DNA sequence to DNA structure (A-DNA or B-DNA)
16	NRDBSM	Non-redundant database of small molecules
17	TPACM4	Partial charge calculator for small molecules
18	Wiener index	Wiener index calculator for small molecules

The results can be downloaded to the PC desktop for further analysis. For this you can use this accompanying website for this purpose:
http://www.scfbio-iitd.res.in/sanjapp/webSearch/Sanjeevini_webpage.html

On more information on how to use the application please visit: http://scfbio-iitd.res.in/sanjapp/webSearch/doc.html
or
http://scfbio-iitd.res.in/sanjeeviniapp/tut.html

Please email us your valuable comments and suggestions at iitd.scfbio@gmail.com

SRBreak: A Read-Depth and Split-Read Framework to Identify Breakpoints of Different Events Inside Simple Copy-Number Variable Regions

Jit — Tue, 15 May 2018 04:42:11 -0500

SRBreak is a read-depth and split-read package written in R for identifying copy-number variants in next-generation sequencing datasets. Note: SBReak was designed to work for multiple samples. It can work for >= 2 samples, but we suggest that users should use >= 5 samples as in the work tested in our paper.

Address of the bookmark: https://github.com/hoangtn/SRBreak

Biotite: A general framework for computational biology

Jit — Mon, 17 Dec 2018 18:52:27 -0600

The package is open source and freely available at GitHub (https://github.com/biotite-dev/biotite). This package is simple to use especially for the beginners in programming and computationally efficient because of the implementation of Numpy and Cython. Biotite consists of four sub packages: sequence, structure, databases, and application. The sequence and structure modules serve for the analysis of sequence and structural data analysis respectively, database downloads files from the other databases such as RCSB PDB, and application provides interface for external software.

The Biotite package bundles popular tasks in computational biology into an unifying framework, which is easy to use on the one hand side, but is also computationally efficient due to intensive usage of NumPy and Cython. This package focuses on working with sequence and structure data and supports various file formats and analysis and manipulation functions.

Address of the bookmark: https://github.com/biotite-dev/biotite

RosettaAntibodyDesign (RAbD): A general framework for computational antibody design

BioStar — Sun, 20 Sep 2020 06:03:42 -0500

RosettaAntibodyDesign (RAbD) is a generalized framework for the design of antibodies, in which a user can easily tailor the run to their project needs. The algorithm is meant to sample the diverse sequence, structure, and binding space of an antibody-antigen complex. It can be used for a multitude of project types, from denovo design to redesigns that improve binding affinity, optimize stability, or manipulate function.

The framework is based on rigorous bioinformatic analysis and rooted very much on our recent clustering of antibody CDR regions. It uses the North/Dunbrack CDR definition as outlined in the North/Dunbrack clustering paper.

More at

https://www.rosettacommons.org/docs/latest/application_documentation/antibody/RosettaAntibodyDesign

https://bio-jade.readthedocs.io/en/latest/installation.html

Address of the bookmark: https://www.rosettacommons.org/docs/latest/application_documentation/antibody/RosettaAntibodyDesign

d3Network:Tools for creating D3 JavaScript network, tree, dendrogram, and Sankey graphs from R.

Jit — Fri, 06 Apr 2018 12:10:45 -0500

Mike Bostock’s D3.js is great for creating interactive network graphs with JavaScript. The d3Network package makes it easy to create these network graphs from R. The main idea is that you should able to take an R data frame with information about the relationships between members of a network and create full network graphs with one command.

Address of the bookmark: http://christophergandrud.github.io/d3Network/

Python and BioPython Tutorial

Manshi Raghubanshi — Fri, 23 Aug 2013 06:47:40 -0500

A quickstart tutorial that allows to become familiar with the Python language. The exercises expect knowledge of basic concepts of programming. A group of 2nd year computer science students with no previous Python knowledge required 60'-90' to complete the exercises. With about 3 hours time, the exercise is suitable for non-programmers as well.

Address of the bookmark: http://www.biotnet.org/training-materials/python-programmers

Type Hinting

Pranjali Yadav — Fri, 09 Jan 2015 22:26:13 -0600

Python creator Guido van Rossum’s proposal for static type-checking annotations is inching closer to reality, and the feature has taken on a new name: type hinting.

Back in August, van Rossum published a proposal on the Python mailing list recommending type-checking annotations as a valuable feature for the next version of Python to improve the performance of editors and IDEs, linter capabilities, standard notation, and refactoring. Van Rossum’s latest proposal, posted late last month, outlined plans to publish a Python Enhancement Proposal (PEP) in early January to put the feature now known as type hinting on track for inclusion in Python 3.5, slated for release this September.

Reference

https://quip.com/r69HA9GhGa7J

Scientist - Computational Genomics (Two Positions)

Sat, 12 Mar 2016 18:07:56 -0600

ICRISAT is a non-profit, non-political organization that conducts agricultural research for development in Asia and sub-Saharan Africa with a wide array of partners throughout the world. Covering 6.5 million square kilometers of land in 55 countries, the semi-arid tropics is home to over 2 billion people, with 650 million of these being the poorest of the poor. ICRISAT and its partners help empower those living in the semi-arid tropics, especially smallholder farmers, to overcome poverty, hunger, malnutrition and a degraded environment through more efficient and profitable agriculture.

ICRISAT is headquartered in Patancheru near Hyderabad, India, with two regional hubs and five country offices in sub-Saharan Africa. ICRISAT, established in 1972, is a member of the CGIAR Consortium. For more details, see www.icrisat.org.

Responsibilities:Design efficient SQL queries for pulling large sequencing projects.
Serve as a technical adviser to the project leadership and provide computational perspective on product design and deliverability.
Develop and oversee a rapid and incremental software development and release schedule.
Design the software architecture, oversee the implementation and evolution of the design on appropriate hardware platforms.
Working collaboratively in a team environment to design, code, test, debug, and document programs for an integrated genomic analysis pipeline in a rapid and incremental software development and release schedule.
Supervise and review code development and ensure that software products meet project objectives in terms of functionality, scalability, robustness and user experience.
Implement and oversee the QA/QC practices to ensure the development team is adhering to quality standards.
Work closely with the application specialist to integrate feedbacks from teams in each CGIAR center into software customization and improvement.
Assist in training of breeders in the CGIAR centers to use software developed.
Personal Profile:

The applicant should have:

Understanding of genomics data and advanced knowledge of Java, and C/C++ as the programming languages and any of the scripting language like perl and/or Python, SQL
High Performance Computing, data architecture, database platforms and QA/QC practices in software engineering.
She/he should have solid experience in software development projects, preferably as a senior programmer or in the software project management role, and in projects involving big data.
Excellent communication skills are needed to work in this multi-disciplinary, multi-location and multi-cultural team.
Ability to mentor colleagues in quality software development practices is desired.
Educational Qualification : Ph. D or Masters Degree in Computational Biology / Computational Genomics or Equivalent with Research Experience in Mentioned Areas.

More at http://www.icrisat.org/careers/

DendroPy: a Python library for phylogenetic computing

Seema Singh — Mon, 23 Apr 2018 05:49:50 -0500

DendroPy is a Python library for phylogenetic computing. It provides classes and functions for the simulation, processing, and manipulation of phylogenetic trees and character matrices, and supports the reading and writing of phylogenetic data in a range of formats, such as NEXUS, NEWICK, NeXML, Phylip, FASTA, etc. Application scripts for performing some useful phylogenetic operations, such as data conversion and tree posterior distribution summarization, are also distributed and installed as part of the libary. DendroPy can thus function as a stand-alone library for phylogenetics, a component of more complex multi-library phyloinformatic pipelines, or as a scripting “glue” that assembles and drives such pipelines.

The primary home page for DendroPy, with detailed tutorials and documentation, is at:

http://dendropy.org/

DendroPy is also hosted in the official Python repository:

http://packages.python.org/DendroPy/

Requirements and Installation

DendroPy 4.x runs under Python 3 (all versions > 3.1) and Python 2 (Python 2.7 only).

You can install DendroPy by running:

More information is available here:

http://dendropy.org/downloading.html

Documentation

Full documentation is available here:

http://dendropy.org/

This includes:

A comprehensive “getting started” primer .

API documentation .

Descriptions of data formats supported for reading/writing .

and more.

Address of the bookmark: https://pypi.org/project/DendroPy/