BOL: Related items

Bioinformatics Research Scientist @ Oklahoma State University (OSU)

Tue, 17 Aug 2021 13:24:39 -0500

This position is an early career research scientist in the area of Bioinformatics to support research projects involving faculty and staff, at Oklahoma State University (OSU). This is a highly technical position that requires a strong research background in biomedical or life sciences, including a high level of expertise with bioinformatics algorithms, databases, and analyses with a focus on next-generation sequence data. Although most of the projects will deal directly with the analysis of DNA and RNA sequence data the individual should be well versed in other types of data sources as well (i.e., microarrays) and handling of large datasets (using data analytics, machine learning, and deep learning techniques).

More at https://okstate.csod.com/ats/careersite/JobDetails.aspx?site=8&id=9874

Molecular and Computational Biology Research School

Fri, 20 Sep 2013 09:01:18 -0500

The ambition of the Molecular and Computational Biology Research School (MCB) is to create an attractive and stimulating training environment for PhD students in molecular and computational biology, both to better serve the needs for relevant training in the field, and to stimulate crossdiscipline developments in the research of the parties.

http://www.uib.no/rs/mcb

Getting Started with Nextflow

LEGE — Sat, 18 Sep 2021 01:28:41 -0500

Introduction to Bioinformatics workflows with Nextflow and nf-core

Getting Started with Nextflow

Objectives Understand

What a workflow management system is.

Understand the benefits of using a workflow management system.

Explain the benefits of using Nextflow as part of your bioinformatics workflow.

Explain the components of a Nextflow script.

Run a Nextflow script.

Introduction to Bioinformatics workflows with Nextflow and nf-core

Getting Started with Nextflow

Address of the bookmark: https://carpentries-incubator.github.io/workflows-nextflow/aio/index.html

Murray Cox's Genomicus Lab

Thu, 26 Sep 2013 16:42:42 -0500

This group interested in modeling genome dynamics in following topics:

---how genetic variation is distributed within and between individuals,
---determining how this diversity changes over evolutionary time.

Hence, Cox group work at the interface between biology, statistics and computer science to address questions of outstanding biological importance through intrepretation of large genetic datasets.

Profile:
Associate Professor Murray Cox,
Inaugural Rutherford Fellow of the Royal Society of New Zealand, Principal Investigator in the BioProtection Research Center and Associate Investigator in the Allan Wilson Center for Molecular Ecology and Evolution
Email : m.p.cox@massey.ac.nz
Webpage: http://massey.genomicus.com/index.html

Bioinfo Lab

Fri, 04 Mar 2022 00:17:00 -0600

The Institute of Bioinformatics conducts internationally renowned research and provides profound education in bioinformatics. Its research focuses on development and application of machine learning and statistical methods in biology and medicine.

Contact:
Computer Science Building (Science Park 3)
Altenberger Str. 69, A-4040 Linz, Austria
Tel. +43 732 2468 4520 / Fax +43 732 2468 4539
E-mail secretary@bioinf.jku.at

http://www.bioinf.jku.at/

04- Informatics Approach to Cancer - Interview with Dr. Joel Saltz

Mon, 07 Oct 2013 14:35:43 -0500

For additional information visit http://www.cancerquest.org/joel-saltz-interview. Dr. Joel Saltz is a Professor in the Departments of Pathology, Biostatistics and Bioinformatics, and Mathematics and Computer Science at Emory University. Dr. Saltz's research on bioinformatics spans several disciplines. One project involves applying computer analysis to medical imaging to yield better results for patients. As an example, a computer program may able to help doctors detect small cancers in a CT scan or mammogram. In this interview segment, Dr. Saltz discusses the informatics approach to cancer. To learn more about cancer and watch additional interviews, please visit the CancerQuest website at http://www.cancerquest.org.

Interesting Bioinformatics Resources !

Abhi — Fri, 11 Nov 2022 06:30:46 -0600

1. a reproducible workflow. https://www.youtube.com/watch?v=s3JldKoA0zw This two minute video will change your mind on reproducible research

2. Parallel sequencing lives, or what makes large sequencing projects successful https://academic.oup.com/gigascience/article/6/11/gix100/4557140?login=false

3. Common-sense approaches to sharing tabular data alongside publication https://www.sciencedirect.com/science/article/pii/S2666389921002300

4. A Reproducible Data Analysis Workflow with R Markdown, Git, Make, and Docker https://psyarxiv.com/8xzqy/

5. Practical Computational Reproducibility in the Life Sciences https://www.cell.com/cell-systems/fulltext/S2405-4712(18)30140-6

6. A video by Dr.Keith A. Baggerly from MD Anderson [The Importance of Reproducible Research in High-Throughput Biology](https://www.youtube.com/watch?v=7gYIs7uYbMo) highly recommended.

7. Ten Simple Rules for Reproducible Computational Research http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003285)

8. Good Enough Practices in Scientific Computing http://arxiv.org/abs/1609.00037

9. Best Practices for Scientific Computing https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1001745

10. A Quick Guide to Organizing Computational Biology Projects http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.100042 A must read for computational biologists!

11. Reproducibility of computational workflows is automated using continuous analysis https://www.nature.com/articles/nbt.3780

12. Five selfish reasons to work reproducibly https://genomebiology.biomedcentral.com/articles/10.1186/s13059-015-0850-7

Evolution and Cancer

Fri, 27 Sep 2013 11:28:49 -0500

Air date: Wednesday, January 04, 2012, 3:00:00 PM Time displayed is Eastern Time, Washington DC Local Category: Wednesday Afternoon Lectures Description: There is a broad consensus that cancer is the result of somatic cells having serially gained, by a series of mutations, the ability to grow independently, to recruit resources from the circulation and the stroma, to invade local tissues, and to found anatomically distant metastases, ultimately killing the host. From the point of view of the cancer-causing somatic cell population, this is evolution driven by mutation and selection. Genomics has resulted in a parallel consensus that the central functions of all eukaryotes are highly conserved, not only at the level of individual protein functions, but also complex biological pathways and systems. These ideas motivated a comparison between results of molecular genetic studies of experimental evolution in yeast and the molecular genetic phenomena associated with tumorigenesis and tumor progression. We find some very striking similarities, including recurring genomic rearrangements, alterations of the regulation of specific growth-promoting genes, population-genetic features that affect the fitness trajectories of growth rate variants in evolving populations, and physiological and metabolic similarities derived from the conservation of the basic plan of growth and cell multiplication among all eukaryotes. It is hoped that some of the insights from yeast will aid the interpretation of sequence changes found in tumors, especially in the urgent necessity to distinguish 'driver' from 'passenger' mutations." David Botstein's fundamental contributions to modern genetics include the development of genetic methods for understanding biological functions and the discovery of the functions of many yeast and bacterial genes. In 1980, Botstein and three colleagues proposed a method for mapping human genes that laid the groundwork for the Human Genome Project. The basic principle of the mapping scheme was to develop, by recombinant DNA techniques, random single-copy DNA probes capable of detecting DNA sequence polymorphisms when hybridized to restriction digests, or specific fragments, of an individual's DNA. The method was used in subsequent years to identify several human disease genes, such as Huntington's and BRCA1. Variations of this method enabled the sequencing phase of the Human Genome Project. In the 1990s Botstein, having moved to Stanford University School of Medicine, collaborated with Patrick O. Brown of Stanford in exploiting DNA microarrays to study genome-wide gene expression patterns in yeast and in human cancers. This required developing a new statistical method and graphical interface, widely used today to interpret genomic data. Botstein also has helped to create, with Michael Ashburner and Gerald Rubin, a bioinformatics initiative to unify the representation of gene and gene product attributes across all species, called Gene Ontology. He graduated from Harvard College and earned his doctorate from the University of Michigan. He worked at Massachusetts Institute of Technology from 1967 to 1988; served as vice president for science at Genentech from 1988 to 1990; chaired the Department of Genetics at the Stanford University School of Medicine from 1990 to 2003; and joined the Princeton University faculty in 2003. He has sat on numerous editorial boards and was the founding editor of Molecular Biology of the Cell. Among recent major awards, Bostein won the Peter Gruber Foundation Prize in Genetics in 2003, the Apple Science Innovator Award in 2008, and the Albany Medical Center Prize in 2010. The NIH Wednesday Afternoon Lecture Series includes weekly scientific talks by some of the top researchers in the biomedical sciences worldwide. For more information, visit: The NIH Director's Wednesday Afternoon Lecture Series Author: Dr. David Botstein, Princeton University Runtime: 00:59:58 Permanent link: http://videocast.nih.gov/launch.asp?17046

Opportunity at McDermott Center Bioinformatics Lab

Sat, 01 Apr 2023 09:56:39 -0500

Our team, composed of experts from diverse backgrounds including genetics, cancer biology, computer science, bioinformatics, and microbiology, stays current with evolving bioinformatics techniques. We offer consulting, customized service, and collaboration opportunities. We suggest visiting us to discuss your experiment design and results, as we can tailor our assistance to meet your specific research goals.

https://labs.utsouthwestern.edu/bioinformatics-lab/positions

Pre- or postdoctoral research fellowship in Structural Bioinformatics in Padova

Wed, 02 Oct 2013 15:12:22 -0500

University of Padova (URL: http://protein.bio.unipd.it/)

A research fellowship is available at the BioComputing Laboratory, University of Padova (URL: http://protein.bio.unipd.it/). A highly motivated and creative candidate is sought to work on structural bioinformatics. Specifically, the project entails the development of novel methods, tools and databases for the analysis of protein structures. The BioComputing Laboratory is a group of a dozen people working on several aspects of prediction of protein structure & function employing techniques at the intersection between biology, medicine, chemistry, physics & computer science. Our aim is to integrate the development of novel methods and their application to biologically relevant problems. We are looking for candidates with a solid Bioinformatics background, programming experience (Python, Perl, C++ and/or Java) and good knowledge of molecular biology (protein structure/function, signalling pathways). Candidates should have a degree with top marks, optionally hold a PhD, and be highly motivated to work on interdisciplinary research. Good knowledge of English, an open-minded spirit, being collaborative and creative are crucial. The fellowship, which should start in late 2013, is initially for one year. It will be commensurate to experience, can be extended depending on performance and may lead to a PhD degree. The successful candidate will be located at the BioComputing Laboratory, University of Padova. Travel support for conferences and/or research visits abroad may be provided. To apply, please send your CV, a brief description of your research background and the names of two (or more) references to Prof. Silvio Tosatto (Email: silvio.tosatto@unipd.it).

Contact Person (Referent): Silvio Tosatto
Ref. E-Mail: silvio.tosatto@unipd.it
Tel: +39 049 827 6269
Fax: +39 049 827 6260
Group Web Page: http://protein.bio.unipd.it/