BOL: Related items

Google Genomics

Reshma Khatun — Fri, 17 Oct 2014 02:14:14 -0500

Google Genomics provides an API to store, process, explore, and share DNA sequence reads, reference-based alignments, and variant calls, using Google's cloud infrastructure.

Store alignments and variant calls for one genome or a million.
Process genomic data in batch by running principal component analysis or Hardy-Weinberg equilibrium, in minutes or hours, by using parallel computing frameworks like MapReduce.
Explore data by slicing alignments and variants by genomic range across one or multiple samples -- for your own algorithms or for visualization; or interactively process entire cohorts to find transition/transversion ratios, allelic frequency, genome-wide association and more using BigQuery.
Share genomic data with your research group, collaborators, the broader community, or the public. You decide.

Google Genomics is implementing the API defined by the Global Alliance for Genomics and Health for visualization, analysis and more. Compliant software can access Google Genomics, local servers, or any other implementation.

Address of the bookmark: https://cloud.google.com/genomics/

Genome U-Plot: a whole genome visualization

Rahul Nayak — Fri, 13 Jul 2018 19:50:41 -0500

Genome U-Plot for producing clear and intuitive graphs that allows researchers to generate novel insights and hypotheses by visualizing SVs such as deletions, amplifications, and chromoanagenesis events. The main features of the Genome U-Plot are its layered layout, its high spatial resolution and its improved aesthetic qualities.

https://github.com/gaitat/GenomeUPlot

Address of the bookmark: https://github.com/gaitat/GenomeUPlot

Research Scientist – National Institute of Cholera and Enteric Diseases

Wed, 22 Oct 2014 10:26:46 -0500

The following post is to be filled up on purely temporary basis under the project entitled "Second phase of Task Force Biomedical Informatics Center of ICMR" under Dr. Santasabuj Das, Scientist 'D' of this Institute:-

01. Scientist II 01
Essential: Ph.D. degree in Life Sciences from a recognized university along with a minimum of 2 years of research experience in Bioinformatics as evidenced by publications in the peer reviewed journals.

OR
Ph.D. degree in Bioinformatics from a recognized university.

OR
M.Sc. in Bioinformatics from a recognized university along with a minimum of 3 years of research experience in Bioinformatics as evidenced by publications in the peer reviewed journals.

Desirable:
Thorough Knowledge about In silico genome analysis and comparative genomics.
Experience with in silico identification of novel virulence factors of pathogens, host-pathogen interactions and Systems Biology.
Additional Postdoctoral research experience in relevant subjects from a recognized institutions.

Rs. 44,000/- p.m. (consolidated) plus 30% HRA

Below 40 years

Applications along with Bio-Data containing detail work experience and full list of publications may be sent via email tosantasabujdas@yahoo.com latest by October 27, 2014.

Short-listed candidates will be called via email for an interview to be held at the institute in the second week of November, 2014.

Advertisement: www.niced.org.in/placements.htm

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/

Celebrating Crystallography - An animated adventure

Fri, 31 Oct 2014 15:59:00 -0500

NEW: Now with French or Spanish subtitles (click on the 'Captions' icon to select). Plus... Watch the French language version here: https://www.youtube.com/watch?v=PvLu7BOsJhM X-ray crystallography is arguably one of the greatest innovations of the twentieth century, but not that many people know what it is or how it came about. Join us on an animated journey through the 100 year history of crystallography -- from the pioneering work of William and Lawrence Bragg in 1913 to the surface of Mars! Narrated by structural biologist Stephen Curry and produced by animation company 12foot6, the film explores the extraordinary history of crystallography. To date 28 Nobel Prizes have been awarded to projects related to the field and X-ray crystallography remains the foremost technique in determining the structures of a huge range of complex molecules. This film was produced in celebration of the Bragg Centenary and was funded by STFC. Watch more science videos on the amazing Ri Channel: http://richannel.org Watch more animations from 12foot6: http://12foot6.com/ The Ri is on Twitter: http://twitter.com/ri_science and Facebook: http://www.facebook.com/royalinstitution Subscribe for the latest science videos: http://richannel.org/newsletter

MitoZ: a toolkit for animal mitochondrial genome assembly, annotation and visualization

Jit — Fri, 24 Jan 2020 04:09:15 -0600

MitoZ is a Python3-based toolkit which aims to automatically filter pair-end raw data (fastq files), assemble genome, search for mitogenome sequences from the genome assembly result, annotate mitogenome (genbank file as result), and mitogenome visualization. MitoZ is available from https://github.com/linzhi2013/MitoZ.

https://academic.oup.com/nar/article/47/11/e63/5377471

Address of the bookmark: https://github.com/linzhi2013/MitoZ

Postdoctoral fellowship in Bioinformatics

Sat, 08 Nov 2014 14:41:14 -0600

A two-year post-doctoral position is available in the Biocomputing group of the Sapienza University led by Anna Tramontano to work on either genomics research or structural bioinformatics, focusing on the study of relevant biomedical problems.
The ideal candidate should be motivated and talented, hold a PhD degree, have good programming skills, a grasp of statistical methods and an understanding of biology.
Experience in the development of computational biology methods would be an added value.

Good communication skills and fluency in spoken and written English are required.
Please apply sending a curriculum vitae, the names of at least two referees and a letter of motivation describing past experience and future goals to anna.tramontano@uniroma1.it with subject: “Application for post-doctoral position November 2014 YOUR LAST NAME”

Deadline: No later than November 28th, 2014.
Duration: 2 years

Salary on grant: Commeasured to the experience of the candidate
Contact Person (Referent): Anna Tramontano
Ref. E-Mail: anna.tramontano@uniroma1.it
Group Web Page: http:/www.biocomputing.it

Tools for Geospatial data analysis !

BioStar — Wed, 22 Mar 2023 02:10:28 -0500

Geospatial data is becoming increasingly important in many fields, including urban planning, environmental science, public health, and more. These tools can help you work with data from a variety of sources, including satellite imagery, GPS data, and other forms of spatial data. They can help you visualize data, perform complex analysis, and even create maps and other visualizations.

The list includes some of the most popular and widely used geospatial tools available in Python. These tools can help you work with data from a variety of sources and in a variety of formats. Some of the tools are focused on visualization, such as Cartopy, Folium, and Contextily, which allow you to create interactive maps and other visualizations. Other tools are more focused on data manipulation and analysis, such as Fiona, GeoPandas, and Rasterio, which allow you to manipulate and analyze spatial data in a variety of ways.

The list also includes some tools for working with specific types of geospatial data. For example, the H3 library is designed specifically for working with hexagonal grids, while PySAL is focused on spatial econometrics and spatial analysis. Whether you are a data scientist, GIS specialist, or geospatial enthusiast, these tools are sure to enhance your work and help you achieve your goals.

In summary, this list is an excellent resource for anyone working with geospatial data in Python. It contains a wide range of tools for working with different types of data, and can help you visualize data, perform complex analysis, and create maps and other visualizations. If you're looking to enhance your skills in geospatial analysis, this list is definitely worth checking out.

These tools are:

ArcGIS - https://lnkd.in/dgC6sKJH
Cartopy - https://lnkd.in/dc8ijXRg
Contextily - https://lnkd.in/dTdQsmKX
Descartes - https://lnkd.in/dCJykxwW
Fiona - https://lnkd.in/d8sJ3Q5a
Folium - https://lnkd.in/dfSsE-MB
GDAL - https://lnkd.in/dYBJBaAY
Geohash - https://lnkd.in/d_NxJ4_M
GeoJSON - https://lnkd.in/daGs2WYq
GeoPandas - https://lnkd.in/dBTFKKV3
Geopy - https://lnkd.in/dfAzR8Xa
Gevent - http://www.gevent.org
H3 - https://h3geo.org/docs/
OSMnx - https://lnkd.in/dm3pHgUS
PyQGIS - https://lnkd.in/dShWyWVr
PySAL - https://pysal.org
Pydeck - https://lnkd.in/dGBFu-iw
Pyproj - https://lnkd.in/dNG9fdkm
RTree - https://lnkd.in/dURMiYpU
Rasterio - https://lnkd.in/dEMC6ve6
Scikit-mobility - https://lnkd.in/dpHhaX2J
Shapely - https://lnkd.in/d568datK

These tools offer a wide range of capabilities for working with geospatial data, from visualizing and manipulating data to performing complex analysis and modeling. Whether you are a data scientist, GIS specialist, or geospatial enthusiast, these tools are sure to enhance your work and help you achieve your goals.

Centre for Systems Biology & Bioinformatics, Panjab University vacancy of Research Fellow

Wed, 12 Nov 2014 06:18:54 -0600

Applications are invited along with complete bio-data and attested copies of certificates of qualifications, experience etc. for the one post of
Research Fellow and one post of Program Assistant under PURSE Grant of the University in Centre for Systems Biology & Bioinformatics, UIEAST, Panjab University, Chandigarh which is tenable till the period of the project

Essential Qualification
For Research Fellow:-
M.Sc. in Systems Biology and Bioinformatics / Life
Sciences with minimum 55% marks.
Preference will be given to NET/GATE/ICMR qualified candidates without fellowship however, candidates who have cleared the Panjab University Ph.D. entrance test in Systems Biology & Bioinformatics will also be eligible.

Applications should be reach on or before 19-11-2014 in the office of the undersigned. Interview will be held on 21-11-2014 in the office of the Coordinator, Centre for Systems Biology & Bioinformatics, South Campus, Block-3, Sector-25, Panjab University, Chandigarh. No TA/DA will be paid.

more at http://jobs.puchd.ac.in/includes/jobs/2014/20141110143634-Advertisement.pdf

NGenomeSyn: an easy-to-use and flexible tool for publication-ready visualization of syntenic relationships across multiple genomes

LEGE — Tue, 10 Sep 2024 04:54:55 -0500

NGenomeSyn: an easy-to-use and flexible tool for publication-ready visualization of syntenic relationships across multiple genomes

NGenomeSyn [multiple (N) Genome Synteny], for publication-ready visualization of syntenic relationships of the whole genome or local region and genomic features (e.g. repeats, structural variations, genes) across multiple genomes with a high customization. NGenomeSyn provides an easy way for its users to visualize a large amount of data with a rich layout by simply adjusting options for moving, scaling, and rotation of target genomes. Moreover, NGenomeSyn could be applied on the visualization of relationships on non-genomic data with similar input formats.

https://academic.oup.com/bioinformatics/article/39/3/btad121/7072460

Address of the bookmark: https://github.com/hewm2008/NGenomeSyn