BOL: Related items

Fundamentals of Data Visualization by Claus O. Wilke

Abhi — Sat, 08 Jun 2024 16:07:19 -0500

The book is meant as a guide to making visualizations that accurately reflect the data, tell a story, and look professional. It has grown out of my experience of working with students and postdocs in my laboratory on thousands of data visualizations. Over the years, I have noticed that the same issues arise over and over. I have attempted to collect my accumulated knowledge from these interactions in the form of this book.

The entire book is written in R Markdown, using RStudio as my text editor and the bookdown package to turn a collection of markdown documents into a coherent whole. The book’s source code is hosted on GitHub, at https://github.com/clauswilke/dataviz.

Address of the bookmark: https://clauswilke.com/dataviz/

BRaVa Browser

Jitendra Narayan — Sun, 23 Aug 2026 10:32:19 -0500

BRaVa Browser is an interactive web tool for exploring rare genetic variant associations. It allows users to search and visualize rare variant association results across genes and traits, making it easier to investigate potential relationships between genetic variation and disease or other phenotypes.

More at https://nikbaya.github.io/brava_browser/#/

Address of the bookmark: https://nikbaya.github.io/brava_browser/#/

Encode sequencing data freely available to download and use for academic means

Rahul Agarwal — Thu, 13 Mar 2014 18:18:08 -0500

In Encode, regulatory elements investigated via DNA hypersensitivity assays, assays of DNA methylation, and chromatin immunoprecipitation (ChIP) of proteins that interact with DNA, including modified histones and transcription factors, followed by sequencing (ChIP-Seq).

More information:

https://genome.ucsc.edu/ENCODE/pilot.html

Address of the bookmark: https://genome.ucsc.edu/ENCODE/

Webinar: Wednesday 21 August 2013 at Noon EDT

Jitendra Narayan — Sun, 11 Aug 2013 19:31:56 -0500

This webinar will describe the use of combinatorial pooling to reconstruct gene sequences within BACs. Recent work in barley has shown that this level of sequence knowledge is sufficient to support critical end-point objectives such as map-based cloning and marker-assisted breeding.

http://www.extension.org/pages/67926/upcoming-webinar:-selective-sequencing-through-combinatorial-pooling#.UggsVuHyPqU

Research Associate (RA) at INSTITUTE OF ADVANCED STUDY IN SCIENCE AND TECHNOLOGY

Mon, 05 May 2014 08:44:24 -0500

INSTITUTE OF ADVANCED STUDY IN SCIENCE AND TECHNOLOGY
(An Autonomous Institute under Department of Science and Technology, Govt. of India)
Paschim Boragaon, Garchuk, Guwahati-781035

Appointment Adv.No.2

Applications in plain paper are invited from Indian citizens for one/two position each of Research Associate, Traineeship and Studentship for BIF facility, Division of Life Sciences, IASST.

Applications with complete Bio-data containing contact address, e-mail and phone number, two recent passport size photographs and attested copies of mark sheets, certificates etc., should be sent to the Registrar, IASST, Paschim Boragaon, Garchuk, Guwahati – 781035, Assam, so as to reach on or before 5/05/2014.

A. Research Associate:

Number of vacancies: 1 (One)

Qualifications:

PhD in Bioinformatics or allied disciplines with knowledge of Bioinformatics. The candidates who have submitted PhD thesis may also apply.

In case, candidates having PhD are not found, candidates having MSc in Bioinformatics or allied disciplines with sound knowledge of Bioinformatics will be preferred.

Remuneration: Candidate having PhD will get a consolidated remuneration of Rs. 22,000/- +HRA per month. MSc having NET/GATE/SLET qualified candidate will get a remuneration of Rs. 16,000/= and HRA and candidate with only MSc will get a remuneration of Rs.14,000/- and HRA.

Tenure:

The post is initially for one year and may be extended depending on the performance till the tenure of the project.

B. Traineeship:

Number of vacancies: 2 (Two)

Qualifications:

Candidate with a postgraduate degree in Bioinformatics/Biotechnology/Life sciences from a recognised University

Remuneration: Rs. 5000/month for 6 months

C. Studentship:

Number of vacancies: 2 (Two)

Qualifications:

Candidate pursuing M.Sc in bioinformatics in a recognised University.

Remuneration: Rs. 5000/month for 6 months

http://iasst.gov.in/pdf/recruitment/advt%20no_2_24042014.pdf

NCBI Gene Screencast

Fri, 30 May 2014 06:21:18 -0500

A short walkthrough of the NCBI Gene page

Genome Stability Laboratory

Mon, 07 Mar 2016 04:16:32 -0600

The bakers yeast, Saccharomyces cerevisiae is an ideal model organism to understand mechanisms of meiotic chromosome segregation. In S. cerevisiae and in mammals, the majority of meiotic crossovers are formed through a highly conserved MSH4p-MSH5p, MLH1p-MLH3p dependent pathway. We are interested in charactering the role of these complexes in crossover formation and distribution among all homolog pairs. Errors in this process are linked to congenital birth defects in humans such as Down's syndrome.Our laboratory is also interested in understanding the effect of genetic background on mutation rate variation using S. cerevisiae as a model. These studies are relevant for understanding cancer progression, genome evolution and architecture. We use high- throughput genomic methods as well as classical genetics to achieve these aims.

More at http://faculty.iisertvm.ac.in/~nishantkt/index.html

NearHGT

Jit — Wed, 22 Jun 2016 05:41:57 -0500

Horizontal gene transfer (HGT), the transfer of genetic material between organisms, is crucial for genetic innovation and the evolution of genome architecture. Existing HGT detection algorithms rely on a strong phylogenetic signal distinguishing the transferred sequence from ancestral (vertically derived) genes in its recipient genome. Detecting HGT between closely related species or strains is challenging, as the phylogenetic signal is usually weak and the nucleotide composition is normally nearly identical. Nevertheless, there is a great importance in detecting HGT between congeneric species or strains, especially in clinical microbiology, where understanding the emergence of new virulent and drug-resistant strains is crucial, and often time-sensitive.

We developed a novel, self-contained technique named Near HGT, based on the synteny index, to measure the divergence of a gene from its native genomic environment and used it to identify candidate HGT events between closely related strains. The method confirms candidate transferred genes based on the constant relative mutability (CRM). Using CRM, the algorithm assigns a confidence score based on “unusual” sequence divergence. A gene exhibiting exceptional deviations according to both synteny and mutability criteria, is considered a validated HGT product. We first employed the technique to a set of three E. coli strains and detected several highly probable horizontally acquired genes. We then compared the method to existing HGT detection tools using a larger strain data set.

When combined with additional approaches our new algorithm provides richer picture and brings us closer to the goal of detecting all newly acquired genes in a particular strain.

Availability: The method is publicly available athttp://research.haifa.ac.il/~ssagi/software/nearHGT.zip

Address of the bookmark: http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004408

PASA: Gene Structure Annotation and Analysis

biogeek — Tue, 26 Dec 2017 21:14:03 -0600

PASA, acronym for Program to Assemble Spliced Alignments, is a eukaryotic genome annotation tool that exploits spliced alignments of expressed transcript sequences to automatically model gene structures, and to maintain gene structure annotation consistent with the most recently available experimental sequence data. PASA also identifies and classifies all splicing variations supported by the transcript alignments.

Address of the bookmark: http://pasapipeline.github.io/

REVIGO: Reduced Visualize gene ontology

Jit — Tue, 31 Jul 2018 05:28:42 -0500

REViGO can take long lists of Gene Ontology terms and summarize them by removing redundant GO terms. The remaining terms can be visualized in semantic similarity-based scatterplots, interactive graphs, or tag clouds. More about REViGO... |

Please enter a list of Gene Ontology IDs below, each on its own line. The GO IDs may be followed by p-values or another quantity which describes the GO term in a way meaningful to you.

Address of the bookmark: http://revigo.irb.hr/