BOL: Related items

DeepHiC: A Generative Adversarial Network for Enhancing Hi-C Data Resolution

Rahul Nayak — Tue, 03 Mar 2020 01:12:47 -0600

DeepHiC is a GAN-based model for enhancing Hi-C data resolution. We developed this server for helping researchers to enhance their own low-resolution data by a few steps of clicks. Ab initio training could be performed according to our published code. We provided trained models for various depth of low-coverage sequencing Hi-C data. The depth of input data is estimated by its distribution comparing with those of the downsampled Hi-C data we used in training

Address of the bookmark: http://sysomics.com/deephic

InCoB 2014

Thu, 07 Nov 2013 17:53:36 -0600

The 13th International Conference on Bioinformatics (InCoB 2014) will be held in Novotel Sydney Brighton Beach, Sydney, New South Wales, Australia. This year, the InCoB will be held earlier from 31st July to 2nd August 2014 to run back-to-back with the International Biophysics Congress 2014 at the Brisbane Convention and Exhibition Centre, Queensland (3-7 Aug).

More at http://incob2014.org/

visNetwork: an R package for network visualization, using vis.js javascript library

Jit — Wed, 09 Jan 2019 11:00:32 -0600

visNetwork is an R package for network visualization, using vis.js javascript library (http://visjs.org/). All remarks and bugs are welcome on github : https://github.com/datastorm-open/visNetwork.

Features

Based on htmlwidgets, so :

compatible with shiny, R Markdown documents, and RStudio viewer

The package proposes all the features available in vis.js API, and even more with special features for R :

easy to use
custom shapes, styles, colors, sizes, …
works smooth on any modern browser for up to a few thousand nodes and edges
interactivity controls (highlight, collapsed nodes, selection, zoom, physics, movement of nodes, tooltip, events, …)
visualize rpart tree

Address of the bookmark: https://datastorm-open.github.io/visNetwork/

List of Bioinformatics Vacancy, Jobs, Opportunity websites

Jitendra Narayan — Tue, 12 Nov 2013 20:04:28 -0600

Bioinformatics cover wide area of biology, and indulge in almost all sort of science related work. Bioinformatician give strong emphasis on open access to biological information as well as Free and Open Source software!!

There are several jobs opening in bioinformatics all around the world, but many of them do not get proper attention due to lack of advertisements, or social connectivity. This bookmark is created for an academic, non-academic, scientists and budding researchers to help and updates the bioinformatics/computational biology jobs links of all know websites around the world.

I also love to stream the live bioinformatics or Computational biology jobs updates using Twitter https://twitter.com/search?q=bioinformatics%20jobs&src=typd

Find out here about exciting job opportunities in the life sciences.

Please add well known bioinformatics jobs websites below in comment section.

Address of the bookmark: http://www.nature.com/naturejobs/science/jobs?utf8=%E2%9C%93&q=bioinformatics&where=&commit=Find+Jobs

Useful links to therapy, disease, drug and drug-target network data:

Jit — Mon, 01 Jun 2020 11:47:51 -0500

Useful links to therapy, disease, drug and drug-target network data:

DrugBank:

a bioinformatics- cheminformatics resource combining detailed drug data with comprehensive drug target information with >4900 drug (~3500 experimental) and >1500 non-redundant protein entries http://www.drugbank.ca/

Drug-Target Network:

network data of 890 drugs and 394 target human proteins http://www.nature.com/nbt/journal/v25/ n10/suppinfo/nbt1338_S1.html

Drug-Therapy Network:

three layers of drug-therapy networks according to the ATC classification http://www.biomedcentral.com/1471-2210/8/5/additional/

FDA Orange Book:

approved drug products with therapeutic equivalence evaluations http://www.fda.gov/cder/ob/HIDdb: Thomson Investigational drugs database including information on 107000 patents, 25000 investigational drugs and 80000 chemical structures http://scientific.thomson.com/products/iddb/HOMIM: a knowledgebase of human genes and genetic disorders http://www.ncbi.nlm.nih.gov/ sites/entrez?db=omim

PDTD:

3D drug target structure database with a target identification option http://www.dddc.ac.cn/pdtd/

Predicted drug targets:

a set of 1383 predicted drug targets http://www.biomedcentral.com/1471-2105/8/353/additional/ [25] Protein ligand network: a network of 4208 ligands and ~15000 binding sites http://pbil.kaist.ac.kr/~parkkw/Lnet/

TDR Targets Database:

identification and ranking targets against neglected tropical diseases http://tdrtargets.org/

Therapeutic Target Database:

lists >1500 therapeutic targets, disease conditions and corresponding drugs http://xin.cz3.nus.edu.sg/group/cjttd/ttd.asp

MATHomics Lab

Tue, 19 Nov 2013 18:17:32 -0600

Mathomics is a collaborative research group of the Center for Mathematical Modeling and the Center for Genome Regulation at University of Chile, created to play a central role in the development of biotechnological projects, providing state of the art bioinformatics and mathematical modeling tools, allowing to face these problems from the point of view of Systems Biology.

Lab page @ http://www.mathomics.cl/

Next generation sequencing(NGS) books

Abhimanyu Singh — Fri, 30 May 2014 04:48:04 -0500

Employing different technologies, the purpose of NGS platform is to decode the identity or modification on the nucleotides. NGS platforms evolve quickly and capture the main stream.

This bookmark is created to provide NGS online books links.

Address of the bookmark: http://en.wikibooks.org/wiki/Next_Generation_Sequencing_%28NGS%29/Print_version

Research Assistant @ University of Hyderabad

Mon, 25 Nov 2013 10:21:26 -0600

University of Hyderabad
Repository for Tomato Genomic Resources
Department of Plant Sciences
Bioinformatics Position in Tomato Functional Genomics

At the Repository for Tomato Genomics Resources, we are working on Tomato Functional Genomics, using TILLING, Insertional Mutagenesis, proteomics, metabolomics approaches to study fruit ripening in tomato. The current aims of the group include using reverse and forward genetics strategies to isolate tomato mutants delayed in ripening, having high lycopene and folate content in tomato fruits and analysis of light and hormonal signal transduction pathways. For recent publications of the group see (Plant Physiol 161: 2085–2101, Plant Physiol 156: 1424-1438; Molecular Plant 3: 854-869; Plant Methods 6: 3; Plant Methods 5:18; Plant Signaling and Behavior 5:11.).

Currently we have one position available in the projects awarded to Prof. R.P. Sharma funded by Dept of Biotechnology. The qualification for this Position is as follows:

Research Assistant: Applicants should have experience in networking using R language and should be able to develop networks using the transcriptome, proteome and metabolite data sets. M.Tech. in Bioinformatics is required. The selected candidate would be paid Rs. 13,000/-pm- consolidated.

Candidates interested in above positions should send a one page statement clearly explaining how their skills are relevant to the position. The candidates should also enclose detailed CV and the name/email id for three referees. The candidates can send their application by email at rameshwar.sharma@uohyd.ac.in and y.sreelakshmi@uohyd.ac.in on or before December 10th, 2013. The position is purely temporary in nature. Shortlisted candidates would be called for interview. No TA/DA would be provided for attending the interview. We also have openings for CSIR-NET JRF candidates for pursuing PhD in above research areas.

Interested candidates with CSIR-NET JRF can send their CV to the above email
addresses.

http://www.uohyd.ac.in/images/recruitment/tomanet_positions_221113.pdf

Will MinION Nanopore sequencing increase the number of Next Generation Sequencing projects?

Strand — Tue, 04 Aug 2015 05:14:07 -0500

Will MinION Nanopore sequencing increase the number of Next Generation Sequencing projects?

BOKU Lab

Wed, 08 Jan 2014 19:33:12 -0600

We are interested in the study of complex systems in living organisms. Novel views augmenting the classical gene by gene approaches are required to overcome the engineered redundancies and combinatorial effects prevalent in higher eukaryotes. We therefore combine work to establish improved quantitative experimental assays, such as microarrays or differential in-gel electrophoresis, and development of modern computational methods, such as hierarchical probabilistic models or integration of heterogeneous data sources, focussed by biological studies in our laboratory and collaborations.

Highlights of our research include:

Optimization of microarray design, probe signal interpretation
Advanced models and tools for expression profiling
State-of-the-art applications and integrated analyses

Lab page @ http://bioinf.boku.ac.at/