BOL: Related items

NanoPack: visualizing and processing long-read sequencing data

Jit — Fri, 10 Aug 2018 18:41:34 -0500

The NanoPack tools are written in Python3 and released under the GNU GPL3.0 License. The source code can be found at https://github.com/wdecoster/nanopack, together with links to separate scripts and their documentation. The scripts are compatible with Linux, Mac OS and the MS Windows 10 subsystem for Linux and are available as a graphical user interface, a web service at http://nanoplot.bioinf.be and command line tools.

https://academic.oup.com/bioinformatics/article/34/15/2666/4934939

Address of the bookmark: https://github.com/wdecoster/nanoQC

FACULTY POSITION at NATIONAL INSTITUTE OF TECHNOLOGY, ROURKELA

Sun, 05 Oct 2014 15:45:13 -0500

NIT, Rourkela, an institute of national importance under Ministry of HRD, Govt. of India invites applications from Indian nationals possessing excellent academic background along with commitment to quality teaching and research for faculty positions at the level of Professor, Associate Professor and Assistant Professor in most branches of Engineering, Science, Management and Humanities as per following table:-

1 Asst. Professor (on Pre-Ph.D. Contract)

2 Asst. Professor (on Contract)

3 Asst. Professor

4 Associate Professor

5 Professor

Life Sciences:-

i)Biochemistry and Molecular Biology; ii)Cell and Developmental Biology; iii)Immunology and Molecular Medicine; (iv) Microbiology and Ecology (v)Bioinformatics Group; vi)Biophysical Sciences

HOW TO APPLY:-

a. Candidates willing to apply for one or more posts are requested to apply online at “http://www.nitrkl.ac.in/ JOBS & TENDERS /Faculty Position” .
b. Persons employed in Government and Semi-Government organizations may apply directly against the standing advertisement. For this the application should be completed online. The printout of the application generated online should be submitted through employer if shortlisted for interview.
c. The online application can be filled in multiple sessions.
d. Candidates are required to check the Institute website from time to time for latest information, application status call for interview, change of dates and final results.
e. Applications shall be received online only. Please do not send application or CV against this advertisement by email or letter mail.

More Info: http://nitrkl.ac.in/Jobs_Tenders/1FacultyPosition/Default.aspx

Hawkeye: an interactive visual analytics tool for genome assemblies

Abhimanyu Singh — Tue, 01 Jan 2019 11:56:17 -0600

Genome sequencing remains an inexact science, and genome sequences can contain significant errors if they are not carefully examined. Hawkeye is our new visual analytics tool for genome assemblies, designed to aid in identifying and correcting assembly errors. Users can analyze all levels of an assembly along with summary statistics and assembly metrics, and are guided by a ranking component towards likely mis-assemblies. Hawkeye is freely available and released as part of the open source AMOS project http://amos.sourceforge.net/hawkeye.

https://genomebiology.biomedcentral.com/articles/10.1186/gb-2007-8-3-r34

Address of the bookmark: http://amos.sourceforge.net/wiki/index.php?title=Hawkeye

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

Research Fellows at CSIR - Institute of Himalayan Bioresource Technology, Palampur, Himachal Pradesh

Tue, 19 May 2015 07:17:32 -0500

CSIR - Institute of Himalayan Bioresource Technology 2 vacancies of Project Fellow

Name of the Post: Project Fellow

No. of the Post: 02 Two

Salary: Rs. 12000/- per month or Rs. 14000/- per month

Age Limit: Max. 28 years as on 10.06.2015 and relaxation as per rules

Required Job Profile:

Candidate must possess first class B.Tech. in bioinformatics or computational biology OR M.Sc. in bioinformatics or computational biology with fifty five percent marks OR M.Tech. in bioinformatics or computational biology with fifty five percent marks.

How to apply:

Eligible and interested candidates should need to appear for walk-in interview on 10.06.2015 at 9:00 am at the above mentioned address.

Refer to http://www.ihbt.res.in/recruit/AdvtNo7_2015.pdf

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.

Big genomic data on Google Cloud Platform

Fri, 17 Oct 2014 02:16:00 -0500

As the cost of DNA sequencing has dropped, the volume of data produced has risen into the petabytes. Google is working with the genomics community to define a standard API for working with big genomic data sets in the cloud. Building on Google Cloud Platform, we show how to store, process, explore and share genomic data using technologies like BigQuery, AppEngine MapReduce, R and more.

GenoFig: a user-friendly application for the visualization and comparison of genomic regions

BioStar — Mon, 05 Aug 2024 23:06:58 -0500

Tool for graphical vizualisation of annotated genetic regions, and homologous regions comparison. It is an independent recoding of Easyfig 2 initially developped by at the S. Beatson Lab [https://mjsull.github.io/Easyfig/]

Download the GenoFig source code using the 'Download' button on top of this page. Cloning is currently not available for people not member of the INRAE French Institution. After decompression, open a terminal in the folder containing the decompressed files and run:

conda env create -f extras/requirements.yml
extras/SETUP.sh

Address of the bookmark: https://forgemia.inra.fr/public-pgba/genofig

CLUSTER INNOVATION CENTER @ UNIVERSITY OF DELHI

Wed, 22 Oct 2014 10:39:49 -0500

Applications for Pre-selection of candidates under ‘Institutions Mode’ for DST-ISPIRE Faculty in Computational Biology/ Systems Biology/ Bioinformatics

Applications are invited for pre-selection of candidates for Ministry of Science and Technology, Department of Science and Technology INSPIRE Faculty Scheme: a component of “Assured Opportunity for Research Career (AORC)” under INSPIRE in the area of computational Biology/Systems Biology/Bioinformatics.

Candidates having done their B.Tech/B.E. and or M.Sc./M.Tech in Computer Science or Biotechnology and Ph.D. in Systems/ Computational Biology or Bioinformatics may apply in the following format prescribed by DST to the Director, Cluster Innovation Center, University Stadium, GC Narang Marg, University of Delhi, Delhi -11107. Detials of other qualification, age limits etc., please visit www.inspire-dst.gov.in.

Application on the prescribed format may be submitted by email to director@cic.du.ac.in before October 25, 2014. Selected candidates shall be called for an interview. The date, time and venue of the interview shall be informed by email/telephone. For more information about Cluster Innovation Center, please visit https://ducic.ac.in.

IPython: Interactive notebooks

Rahul Nayak — Fri, 07 Nov 2014 12:07:02 -0600

The IPython Notebook is a web-based interactive computational environment where you can combine code execution, text, mathematics, plots and rich media into a single document.

These notebooks are normal files that can be shared with colleagues, converted to other formats such as HTML or PDF, etc. You can share any publicly available notebook by using the IPython Notebook Viewer service which will render it as a static web page. This makes it easy to give your colleagues a document they can read immediately without having to install anything.

To learn more about using the IPython Notebook, you can visit our example collection, and you can read the documentation for all the details on how to use and configure the system. The Notebook Gallery showcases many interesting notebooks covering a variety of topics, from basic programming to advanced scientific computing.

More http://www.nature.com/news/interactive-notebooks-sharing-the-code-1.16261

http://ipython.org/ipython-doc/1/interactive/notebook.html

Reference http://ipython.org/notebook.html