BOL: Related items

Human Genome Meeting 2014, Geneva, Switzerland

Fri, 20 Sep 2013 12:36:44 -0500

The spectacular advances of the last few years resulted in the rapid analysis of the genome sequence of each individual. The biomedical world is now faced with the enormous challenges of assigning pathogenicity to each genomic variant, the functional analysis of the genome of each individual, and the accurate and detailed phenotypic characterization. Advances in these challenges are likely to fundamentally change the medical practice in a global scale.

This 2014 HUGO Meeting in Geneva will be a Forum for discussions on innovative approaches, and proposals to tackle the anticipated challenges.

Time : 27 April 2014 - 30 April 2014

For enquiries, please email hugo2014@mci-group.com or visit www.hugo-international.org

More at http://www.hgm2014-geneva.org/

Frequently used bioinformatics tools for viral genome analysis !

Neel — Wed, 23 Jun 2021 07:40:41 -0500

IVA: accurate de novo assembly of RNA virus genomes.
Hunt M, Gall A, Ong SH, Brener J, Ferns B, Goulder P, Nastouli E, Keane JA, Kellam P, Otto TD.
Bioinformatics. 2015 Jul 15;31(14):2374-6. doi: 10.1093/bioinformatics/btv120. Epub 2015 Feb 28.

Adapter sequences:
Optimal enzymes for amplifying sequencing libraries.
Quail, M. a et al. Nat. Methods 9, 10-1 (2012).

GAGE:
GAGE: A critical evaluation of genome assemblies and assembly algorithms.
Salzberg, S. L. et al. Genome Res. 22, 557-67 (2012).

KMC:
Disk-based k-mer counting on a PC.
Deorowicz, S., Debudaj-Grabysz, A. & Grabowski, S. BMC Bioinformatics 14, 160 (2013).

Kraken:
Kraken: ultrafast metagenomic sequence classification using exact alignments.
Wood, D. E. & Salzberg, S. L. Genome Biol. 15, R46 (2014).

MUMmer:
Versatile and open software for comparing large genomes.
Kurtz, S. et al. Genome Biol. 5, R12 (2004).

R:
R: A language and environment for statistical computing.
R Core Team (2013). R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/.

RATT:
RATT: Rapid Annotation Transfer Tool.
Otto, T. D., Dillon, G. P., Degrave, W. S. & Berriman, M. Nucleic Acids Res. 39, e57 (2011).

SAMtools:
The Sequence Alignment/Map format and SAMtools.
Li, H. et al. Bioinformatics 25, 2078-9 (2009).

Trimmomatic:
Trimmomatic: A flexible trimmer for Illumina Sequence Data.
Bolger, A. M., Lohse, M. & Usadel, B. Bioinformatics 1-7 (2014).

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

Postdoc position at Kiel University, Germany

Sat, 28 Aug 2021 01:16:55 -0500

In the Genomic Microbiology Group of Prof. Tal Dagan at the Institute
of Microbiology at Kiel University, Germany, a

Postdoc position (m/w/d)

in the field of computational evolutionary microbiology is available
for an initially limited period of 36 months at the earliest possible
date. The weekly working time corresponds to 100% of full employment
(If the legal requirements under collective bargaining law are met, the
tariff grouping is carried out up to pay scale 13 TV-L. The obligation
to teach amounts to 4 hours.

The Genomic Microbiology Group research interests are focused on
microbial genome evolution with an emphasis on the study of lateral gene
transfer. In our research we use both computational and experimental
approaches (see www.uni-kiel.de/genomik). The position offers the
opportunity to develop an independent research profile within the group
research focus. The successful applicant is expected to be involved
in teaching of bioinformatics and molecular evolution, including the
development of teaching materials (lectures/exercises/short videos).

Your profile:
· Doctoral or PhD degree in Molecular Evolution, Bioinformatics or
related fields.
· Knowledge and experience in programming (e.g., Python) and
biostatistical analysis (e.g., with R or MatLab).
· Any of the following expertise is an advantage: the analysis of
genomic or transcriptomic data, phylogenetic reconstruction,
comparative genomics.
· Good oral and written communication skills in English.
· Ability to teach in German is an advantage (alternatively, an
indication to do so from the 2nd year on).
· Skills and motivation to communicate and interact with other
scientists.

The Christian-Albrechts-University sees itself as a modern and
cosmopolitan employer. We welcome your application regardless of your age,
gender, cultural and social background, religion, ideology, disability
or sexual identity. We promote equality of the sexes.

The Christian-Albrechts-University is committed to the employment of
people with disabilities. Preference will be given to applications from
severely handicapped persons and persons of equal standing, provided
they are suitable.

We expressly welcome applications from people with a migration background.

For enquiries regarding the position, teaching obligations and research
topic please contact Prof. Tal Dagan: tdagan@ifam.uni-kiel.de.

Applications should be submitted by email to Mrs. Haacks
(dhaacks@ifam.uni-kiel.de) as a single PDF and include: (1) a letter of
motivation (max 1 page, Arial 11, line spacing 1.15), (2) CV, (3) PhD
certificate. Please use 'GMG postdoc application - [your name]'
as a subject.

Please, refrain from sending us application photos.

Application deadline: August 31 2021 or until the position is
filled. Interviews will take place during September/October 2021. The
planned starting date for the position is flexible (but in 2021).

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

16sRNA Database Download

LEGE — Wed, 24 Apr 2024 04:33:15 -0500

Downloading 16S rRNA databases can be crucial for various bioinformatics analyses, especially in microbiome research. However, it's important to note that databases can vary based on your specific needs, such as the taxonomic coverage you require or the type of analysis you're performing. Here's a general guideline on how you can obtain 16S rRNA databases:

NCBI (National Center for Biotechnology Information):
- NCBI provides various databases related to genetic information, including 16S rRNA sequences.
- You can access the 16S ribosomal RNA sequences from NCBI's Nucleotide database (https://www.ncbi.nlm.nih.gov/nucleotide/).
- Perform a search using keywords like "16S rRNA" or specific bacterial names to find relevant sequences.
- You can download sequences individually or in batches using the provided tools.
GreenGenes:
- GreenGenes is a widely used 16S rRNA gene sequence database.
- You can access it at http://greengenes.secondgenome.com/.
- GreenGenes provides precompiled databases for various purposes, including classification, alignment, and phylogenetic analysis.
SILVA:
- SILVA (https://www.arb-silva.de/) is another comprehensive database for ribosomal RNA (rRNA) sequences.
- It covers not only 16S rRNA but also other ribosomal RNA sequences.
- SILVA provides precompiled databases for various purposes, including taxonomic classification and alignment.
Ribosomal Database Project (RDP):
- RDP (http://rdp.cme.msu.edu/) is a curated database that offers 16S rRNA sequences.
- It provides tools for sequence analysis and classification.
- You can download sequences and taxonomy information from their website.
QIIME (Quantitative Insights Into Microbial Ecology):
- QIIME (https://qiime2.org/) is a widely used bioinformatics platform for microbiome analysis.
- It provides tools for analyzing microbial communities, including processing 16S rRNA sequences.
- QIIME often includes its own preprocessed 16S rRNA databases that can be used for analysis within the platform.

Before downloading any database, make sure to read the terms of use and citation requirements, as some databases may have specific usage policies. Additionally, consider the compatibility of the database with your analysis pipeline and software tools.

NCBI 16s RNA database location ftp://ftp.ncbi.nih.gov/blast/db/16SMicrobial.tar.gz

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.

Tigers genome sequenced

Rahul Agarwal — Tue, 17 Sep 2013 16:48:24 -0500

Fifteen scientists led by Dr Jong Bhak of Genome Research Foundation, South Korea, decoded as many as 3 billion nucleotides (organic molecules that form the basic building blocks of nucleic acids, such as DNA). They identified 20,000 genes related to various functions of the tiger.

The biggest and perhaps most fearsome of the world's big cats, the tiger, shares 95.6 percent of its DNA with humans' cute and furry companions, domestic cats.

The new research showed that big cats have genetic mutations that enabled them to be carnivores. The team also identified mutations that allow snow leopards to thrive at high altitudes.

Reference:

http://www.nbcnews.com/science/your-cat-ferocious-tigers-share-lot-95-6-percent-their-4B11182690

http://timesofindia.indiatimes.com/home/environment/flora-fauna/Gene-mapping-of-tiger-completed/articleshow/22671681.cms

Paper:

http://www.nature.com/ncomms/2013/130917/ncomms3433/full/ncomms3433.html

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

Opera: An optimal genome scaffolding program

Jit — Mon, 27 Nov 2017 10:18:20 -0600

Opera (Optimal Paired-End Read Assembler) is a sequence assembly program (http://en.wikipedia.org/wiki/Sequence_assembly ). It uses information from paired-end or long reads to optimally order and orient contigs assembled from shotgun-sequencing reads.

An updated version called OPERA-LG has been re-engineered with features for the assembly of large and complex genomes.

Song Gao, Denis Bertrand, Burton K. H. Chia and Niranjan Nagarajan. OPERA-LG: efficient and exact scaffolding of large, repeat-rich eukaryotic genomes with performance guarantees. Genome Biology, May 2016, doi: 10.1186/s13059-016-0951-y.

Song Gao, Wing-Kin Sung, Niranjan Nagarajan. Opera: reconstructing optimal genomic scaffolds with high-throughput paired-end sequences. Journal of Computational Biology, Sept. 2011, doi:10.1089/cmb.2011.0170.

https://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-0951-y

Address of the bookmark: https://sourceforge.net/projects/operasf/