BOL: Related items

Bioinformatician Dreams

Jitendra Narayan — Wed, 21 Aug 2013 10:50:45 -0500

Bioinformatician life is interconnected, they always dream for a powerful server, little more space on server as they are generating lots of data per run, dream to publish results in good impact journals, meetings reminders :) and research analysis off course!!!

Machine learning training and courses in bioinformatics !

Rahul Nayak — Tue, 31 Dec 2019 19:33:07 -0600

Machine learning techniques have been successful in analyzing biological data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. In this class, we will learn basics about probabilistic models and machine learning techniques. We will focus on probabilistic models (Markov models, Hidden Markov models, and Bayesian networks) for biological sequence analysis and systems biology. Other machine learning techniques, such as Naive bayes, neural networks and SVMs will only be covered briefly.

More at http://homes.sice.indiana.edu/yye/lab/teaching/spring2017-I529/

BIOINFORMATICS

Wed, 28 Aug 2013 19:16:33 -0500

This is a promo video for the brand new cross-boarder branch of study - BIOINFORMATICS. It´s a co-operation between Johannes Kepler University in Linz (Austria) and University of South Bohemia in České Budějovice (Czech Republic). Written, Edited and Directed by, DOP, VFX: Jan Míka Sound by: Mirek Šmilauer Narrator: Jack Bright Produced by: FILMOFON (http://www.filmofon.cz) Released: Nov 2012

Bioinformatician on Valentine's Day

BioQueen — Sun, 14 Feb 2021 11:36:32 -0600

Once asked to a bioinformatician "How is ur Valentine's Day?"

Bioinformatician replied:
if ($date == "Valentine's Day" && $me =! Bioinformatician) {
rose_day(); promise_day(); kiss_day();
}
else {
hack_genome(); ko-fi(); youtube(); do_scripting(); sleep();
)

R and Bioconductor Tutorial

Jitendra Narayan — Fri, 23 Aug 2013 08:23:59 -0500

This tutorial is intended to introduce users quickly to the basics of R, focusing on a few common tasks that biologists need to perform some basic analysis: load a table, plot some graphs, and perform some basic statistics. More extensive tutorials can be found on the project website and via bioconductor (not covered here).

You can add more tutorial links in comments if found new pages.

Address of the bookmark: http://manuals.bioinformatics.ucr.edu/home/R_BioCondManual

Sequence Ontology Bioinformatics Analysis (SOBA) tool to provide a simple statistical and graphical summary of an annotated genome

BioStar — Wed, 22 Jul 2020 10:11:13 -0500

We have developed the Sequence Ontology Bioinformatics Analysis (SOBA) tool to provide a simple statistical and graphical summary of an annotated genome. We envisage its use during annotation jamborees, genome comparison and for use by developers for rapid feedback during annotation software development and testing. SOBA also provides annotation consistency feedback to ensure correct use of terminology within annotations, and guides users to add new terms to the Sequence Ontology when required. SOBA is available at http://www.sequenceontology.org/cgi-bin/soba.cgi.

More at https://pubmed.ncbi.nlm.nih.gov/20494974/

Address of the bookmark: http://www.sequenceontology.org/cgi-bin/soba.cgi

Chang lab

Tue, 24 Sep 2013 17:25:49 -0500

The Chang lab is focused on how the activities of hundreds or even thousands of genes (gene parties) are coordinated to achieve biological meaning. We have pioneered methods to predict, dissect, and control large-scale gene regulatory programs; these methods have provided insights into human development, cancer, and aging. A particular interest is how cells know and remember their locations in the body, particularly with the help of long noncoding RNAs.

More at http://changlab.stanford.edu/index.html

Sr. Scientist Bioinformatics Vacancies at Indian Institute of Toxicology Research, India

Tue, 01 Sep 2020 07:21:04 -0500

Start date of online Registration: Wednesday August 19, 2020 11:00 Hrs IST
Last date for Registration: Monday September 21, 2020 17:30 Hrs IST
Last date for submission of online application: Monday September 21, 2020 17:30 Hrs IST
Last date of Receipt of physical copy of application at CSIR-IITR: Tuesday October 05, 2020 17:30 Hrs IST

Pay Matrix Level-12
No. of Post-01
(UR)
Post – Sr. Scientist
Area Bioinformatics
Age limit : 37 years
PhD in Computational Biology/Bioinformatics with 2 years experience in desired area
Or
ME/M.Tech in Bioinformatics or Genome Informatics or Genetic Engineering with 3 years experience in desired area
Experience of understanding fundamental science behind Artificial Intelligence, machine learning, novel Artificial Intelligence algorithms and architectures, software engineering principles for Artificial Intelligence, natural language processing with proficiency in programming as evident by publications in SCI journals with high impact factor. To be part a group of scientists working in the area of genomics, running the central
bioinformatics facility, developing independent projects and providing bioinformatics support to the user scientists of the Institute.

More at

http://14.139.62.50/CSIR-IITR%20Scientist%20Recruitment%20Adv%202020.pdf

Bioinformatics jobs at Acrannolife

Sun, 25 Oct 2020 22:51:35 -0500

Acrannolife are looking for skilled Bioinformatics Scientists with a minimum of 2yrs Experience in NGS data analysis including Nanopore Sequencing.

This is an opportunity to work on projects that would fundamentally alter the way certain chronic conditions are treated and monitored.

About acrannolife:

We are a team of Post Docs, PhDs, Engineers, Clinicians, and MBAs working towards a future where biology intersects with software(Computational Biology).

We are incubated in Atal Incubation Centre - CCMB and have been backed by some of the leading thought leaders ranging from business to clinical practices.

Interested candidates can fill this form. https://lnkd.in/gtq47hy

and send their CV to hr@acrannolife.com

PostDocs positions in computer science in HELSINKI, FINLAND

Fri, 06 Sep 2013 10:11:19 -0500

Several university departments in the Helsinki region, Finland, are looking for postdoctoral researchers in the field of computer science and information technology. Jobs are available at:
· Helsinki Institute for Information Technology HIIT, Aalto University and University of Helsinki, http://www.hiit.fi
· Department of Computer Science, University of Helsinki, http://www.cs.helsinki.fi
· Department of Information and Computer Science, Aalto University, http://ics.aalto.fi
· Department of Computer Science and Engineering, Aalto University, http://cse.aalto.fi
· Department of Mathematics and Statistics, University of Helsinki, http://mathstat.helsinki.fi/english/

Why Helsinki?
The collaborating Aalto University and University of Helsinki form a leading hub of computer science and modelling, including Machine learning, Data mining, Algorithms, Computational Logic, Cloud computing, Distributed computing, Human-centric ubiquitous ICT, Bioinformatics, etc.
Helsinki region is a safe, pleasant and attractive place to live in, with well-functioning services such as public transport etc. Finland has a comprehensive social security and health care system, including exceptionally good parental leaves, and children's day care services.

Positions are offered in:
Algorithm engineering (String Algorithms group)
Algorithmic bioinformatics (Genome-Scale Algorithmics group)
Automated reasoning and search, especially propositional logic (Computational Logic group)
Computational astrophysics and/or data analysis (Computational Methods and Data Analysis for Astrophysics group)
Computational biology and statistical methods in bioinformatics (Computational Systems Biology group)
Computational creativity and data mining (Discovery group)
Dynamic and large-scale networked systems (Data Communications Software group)
Intelligent multimodal information access (Content-Based Image and Information Retrieval Group)
Machine learning and neuroscience (Statistical Machine Learning group)
Machine learning for structured data (Kernel Machines, Pattern Analysis and Computational Biology group)
Machine learning methods for infectious disease epidemiology (Bayesian Statistics Group)
Probabilistic modeling and machine learning (Complex Systems Computation group)
Statistical machine learning (Statistical Machine Learning group)
Analysing ubiquitous sensor data (HIIT-Wide Focus Area)
Interactive visualization (HIIT-Wide Focus Area)
Affective computing and BCI (HIIT-Wide Focus Area)
Intelligent user interfaces and/or recommender systems (HIIT-Wide Focus Area)
Information retrieval and HCI (HIIT-Wide Focus Area)
Machine learning and data analysis, especially information retrieval, HCI, text and context data (HIIT-Wide Focus Area)
Probabilistic modeling and data analysis for bioinformatics (HIIT-Wide Focus Area)

More at http://www.hiit.fi/postdoc-call-2013