BOL: Related items

‘dockr’: the R container

Jit — Mon, 23 Dec 2019 09:56:49 -0600

dockr 0.8.6 is now available on CRAN. dockr is a minimal toolkit to build a lightweight Docker container image for your R package, in which the package itself is available. The Docker image seeks to mirror your R session as close as possible with respect to R specific dependencies. Both dependencies on CRAN R packages as well as local non-CRAN R packages will be included in the Docker container image.

If you want to know, how Docker works, and why you should consider using Docker, please take a look at the Docker website.

Address of the bookmark: https://www.docker.com/why-docker

New Machine Learning Packages in R

Rahul Nayak — Fri, 27 Mar 2020 12:11:21 -0500

Machine Learning

autokeras v1.0.1: Implements an interface to AutoKeras, an open source software library for automated machine learning. See README for an example.

MTPS v0.1.9: Implements functions to predict simultaneous multiple outcomes based on revised stacking algorithms as described in Xing et al. (2019). See the vignette to get started.

quanteda.textmodels v0.9.1: Implements methods for scaling models and classifiers based on sparse matrix objects representing textual data. It includes implementations of the Laver et al. (2003) wordscores model, the Perry & Benoit’s (2017) class affinity scaling model, and the Slapin & Proksch (2008) wordfish model. See the vignette to get started.

SeqDetect v1.0.7: Implements the automaton model found in Krleža, Vrdoljak & Brčić (2019) to detect and process sequences. See the vignette for examples and theory.

studyStrap v1.0.0: Implements multi-Study Learning algorithms such as Merging, Study-Specific Ensembling (Trained-on-Observed-Studies Ensemble), the Study Strap, and the Covariate-Matched Study Strap. and offers over 20 similarity measures. See Kishida, et al. (2019) for background and the vignette for how to use the package.

Project Fellow Bioinformatics at Central University of Himachal Pradesh

Tue, 09 Feb 2016 03:58:00 -0600

Project Fellow Bioinformatics

Eligibility : MSc(Bio-Chemistry, Bio-Informatics)

Location : Kulu

Last Date : 07 Mar 2016

Hiring Process : Face to Face Interview
Central University of Himachal Pradesh

Project Fellow Bioinformatics Job in Central University of Himachal Pradesh

Project (MRP) entitled: “A project proposal on targeting novel prokaryotic ubiquitin like post-translational modification pathway for therapeutic interventions against Mycobacterium tuberculosis” (No. MRP-MAJOR-MICR-2013-26840)

Essential Qualification: 1. Master degree in Bioinformatics/Biochemistry/Biotechnology/Environmental Science/Microbiology or any branch of Life Sciences with a minimum of 55% marks for general category (50% in case of SC/ST/PH) 2. UGC/CSIR NET, GATE qualified candidates will be given preference. Desirable Qualification: Experience in basic Bioinformatics and Molecular Biology techniques.

Age: Below 40 years as on 01/10/2015.

No.of Post: 1

Salary: NET/GATE qualified candidate: Rs. 16,000/-p.m. for initial two years and Rs. 18,000/- p.m. for the third year. Non-NET/GATE candidates: Rs. 14,000/-p.m. for initial two years and Rs. 16,000/-p.m. for the third year.

Mode of Selection: The selection shall be made on the basis of merit. The eligible candidates are required to appear for interview before the duly constituted Selection Committee for the purpose. The scheduled date, time and venue for the interview shall be intimated to the eligible candidates through phone/ e-mail.
How to apply

Last date for the receipt of applications is 07.03.2016.

More at http://www.cuhimachal.ac.in/news_all.aspx

R Shiny in Life Sciences – Top 7 Dashboard Examples

Neel — Fri, 01 Apr 2022 19:05:03 -0500

R Shiny is one of the easiest ways for developers to make production-ready dashboards when speed and functionality are crucial. Shiny is approachable with a lot of documentation available, and because of this, a lot of developers/researchers with non-coding backgrounds are able to produce some impressive results. The whole ecosystem is easy to get your head around and pretty much limitless with regard to what you can do.

Address of the bookmark: https://www.r-bloggers.com/2022/03/r-shiny-in-life-sciences-top-7-dashboard-examples/

Centurion

Jit — Fri, 12 Feb 2016 04:45:41 -0600

Although centromeres are essential for life and are the subject of extensive research, centromere locations in yeast genomes are difficult to infer, and in most species they are still unknown. Recently, the chromatin conformation assay Hi-C has been re-purposed for diverse applications, including de novo genome assembly, deconvolution of metagenomic samples, and inference of centromere locations. We describe a method, Centurion, that jointly infers the locations of all centromeres in a single yeast genome by exploiting the centromeres’ tendency to cluster in 3D space. We first demonstrate the accuracy of Centurion in identifying known centromere locations from high coverage Hi-C data of budding yeast and a human malaria parasite. We then use two metagenomic samples with relatively low coverage Hi-C data to infer centromere locations for each chromosome in 14 different yeast species. For yeasts with large centromeres (e.g., S. pombe) Centurion predicts the exact centromere locations. For seven yeasts with point centromeres, Centurion predicts most of the centromeres at an average of 5~kb distance from their known locations. Finally, we predict centromere coordinates for six yeast species that currently lack centromere annotations. These results suggest that Centurion can be used for centromere identification for a large number of yeast species, even with a limited amount of Hi-C sequencing.

Paper:http://www.ncbi.nlm.nih.gov/pubmed/25940625

More at http://cbio.ensmp.fr/centurion/

Address of the bookmark: http://cbio.ensmp.fr/centurion/

I-PV: Interactive Protein Sequence Visualization

Jit — Mon, 03 Jul 2017 07:52:51 -0500

I-PV is a interactive data visualization software designed for inspection of protein sequences and mutation information. It is mainly used for Genetics and Bioinformatics. So what exactly makes it standout?

http://i-pv.org/ipv_rec

Address of the bookmark: http://i-pv.org/

Radka Reifová Lab

Mon, 15 Feb 2016 06:00:48 -0600

We are generally interested in the mechanisms of species origin from a molecular and ecological perspective. Particularly, we are interested in the role of sex chromosomes in speciation. Most of our research is done on birds and mammals. Currently, we focus our research on two hybridizing song birds, the Common nightingale (Luscinia megarhynchos) and the Thrush Nightingale (L. luscinia). Combining population genomic and ecological approaches we try to elucidate the genetic architecture of reproductive isolation and understand the role of interspecific competition and song convergence in the evolution of reproductive isolation between the species.

More at http://web.natur.cuni.cz/~radkas/index.php?page=research

D3 javascript for visualization !

Jit — Mon, 23 Apr 2018 08:42:22 -0500

Welcome to the D3 gallery! More examples are available on bl.ocks.org/mbostock. If you want to share an example and don't have your own hosting, consider using Gist and bl.ocks.org. If you want to share or view live examples try vida.io.

Address of the bookmark: https://github.com/d3/d3/wiki/Gallery

RAVEN: a software suite for Matlab that allows for semi-automated reconstruction of genome-scale models

Jit — Wed, 24 Oct 2018 22:38:05 -0500

The RAVEN (Reconstruction, Analysis and Visualization of Metabolic Networks) Toolbox 2 is a software suite for Matlab that allows for semi-automated reconstruction of genome-scale models (GEMs). It makes use of published models and/or KEGG, MetaCyc databases, coupled with extensive gap-filling and quality control features. The software suite also contains methods for visualizing simulation results and omics data, as well as a range of methods for performing simulations and analyzing the results. The software is a useful tool for system-wide data analysis in a metabolic context and for streamlined reconstruction of metabolic networks based on protein homology.

Address of the bookmark: https://github.com/SysBioChalmers/RAVEN

SynVisio: An Interactive Multiscale Synteny Visualization Tool for McScanX.

Jit — Sun, 31 May 2020 02:01:14 -0500

SynVisio lets you explore the results of McScanX a popular synteny and collinearity detection toolkit and generate publication ready images.

SynVisio requires two files to run:

The simplified gff file that was used as an input for a McScanX query.
The collinearity file generated as an output by McScanX for the same input query.
Optional track file in bedgraph format to annotate the generated charts.

SynVisio offers different types of visualizations such as Linear Parallel plots, Hive plots, Stacked Parallel Plots and Dot plots. Users can configure the type of plots required and then choose the source and the target chromosomes that need to be mapped. Users also have option to download the generated visualizations in publication ready SVG or PNG formats.

Address of the bookmark: https://synvisio.github.io/#/