BOL: Related items

Bioinformatics tools for genome assembly !

BioStar — Mon, 24 Jul 2023 07:04:26 -0500

There are numerous genome assembly tools available, each with its strengths and weaknesses. Here is a list of some widely used genome assembly tools as of my last update in September 2021:

SPAdes: An assembler specifically designed for single-cell and multi-cell bacterial genomes, as well as small eukaryotic genomes.
ABySS: A parallelized assembler for large genomes that uses de Bruijn graphs.
Velvet: Another de Bruijn graph-based assembler optimized for short-read sequencing data.
SOAPdenovo: A de Bruijn graph-based assembler designed for short reads, widely used for assembling large and complex genomes.
MaSuRCA: A hybrid assembler that combines data from multiple sequencing technologies, such as Illumina and PacBio.
Canu: A long-read assembler optimized for PacBio and Oxford Nanopore sequencing data.
Flye: A long-read assembler suitable for bacterial and small eukaryotic genomes.
SMARTdenovo: An assembler designed for long reads, particularly suited for PacBio data.
SPAdes Long Read (SPAdesLR): An extension of SPAdes for long-read data, such as those from PacBio or Nanopore.
Minia: An assembler optimized for low memory consumption, suitable for small and medium-sized genomes.
Unicycler: A hybrid assembler that combines short and long reads for circular bacterial genome assembly.
wtdbg2: A de Bruijn graph assembler for long reads, efficient for very large genomes.
Shasta: A long-read assembler that uses the Overlap-Layout-Consensus approach, suitable for PacBio and Nanopore data.
Sparc: An assembler designed to handle noisy long reads from Nanopore sequencing.
CANA: An assembler for metagenomic data, particularly for complex and diverse microbial communities.
Ra Assembler: A metagenome assembler for long reads, designed for highly complex metagenomic samples.

Please note that the field of bioinformatics is constantly evolving, and new assembly tools may have emerged since my last update. Additionally, the performance of these tools can vary depending on the characteristics of the sequencing data and the genome being assembled. When selecting an assembly tool, consider the specific requirements of your project, the available data types, and the computational resources at your disposal. Always refer to the respective tool's documentation and publications for the most up-to-date information and recommendations.

BioKit: a set of tools dedicated to bioinformatics, data visualisation

Neel — Tue, 18 Jun 2024 02:04:39 -0500

BioKit is a set of tools dedicated to bioinformatics, data visualisation (biokit.viz), access to online biological data (e.g. UniProt, NCBI thanks to bioservices). It also contains more advanced tools related to data analysis (e.g., biokit.stats). Since R is quite common in bioinformatics, we also provide a convenient module to run R inside your Python scripts or shell (:mod:biokit.rtools module).

Address of the bookmark: https://biokit.readthedocs.io/en/latest/index.html

Bioinformatics Codes Search

Jitendra Narayan — Thu, 15 Aug 2013 11:08:52 -0500

I bet, this website will be your best friend in near future. This helps us to explore the existing open source codes and learn from it.

You can find some useful open source bioinformatics codes for your analysis work. You can use the left bar options to filtere out or narrow down your search result. This webpage can be an useful resource for a beginners bioinformatician as it contain several bioinformatics basics script that are commonly used by biological programmers and biologist.

Stand on the slumped, dandruff-covered shoulders of millions of computer nerds. _/\_

Enjoy the code and research work.

http://code.ohloh.net/search?s=bioinformatics

Address of the bookmark: http://code.ohloh.net/search?s=bioinformatics

Programming language to build synthetic DNA

Jit — Mon, 30 Sep 2013 16:37:24 -0500

A team led by Georg Seelig (http://homes.cs.washington.edu/~seelig/index.html) at University of Washington has developed a programming language for chemistry that it hopes will streamline efforts to design a network that can guide the behavior of chemical-reaction mixtures in the same way that embedded electronic controllers guide cars, robots and other devices. In medicine, such networks could serve as “smart” drug deliverers or disease detectors at the cellular level.

Reference & More @

http://www.nature.com/nnano/journal/vaop/ncurrent/full/nnano.2013.189.html

http://www.washington.edu/news/2013/09/30/uw-engineers-invent-programming-language-to-build-synthetic-dna/

Image source: washington.edu

Research assistant in computational biology

Wed, 24 Jun 2015 07:55:16 -0500

http://www.au.dk/en/about/vacant-positions/scientific-positions/stillinger/Vacancy/show/743161/5283/

Qualifications:
MSc degree in computer science, engineering, genetics or similar field with a strong emphasis on computational methods.

Deadline
01.08.2015

Which are the best statistical programming languages to study for a bioinformatician?

Jitendra Narayan — Wed, 10 Jul 2013 14:35:34 -0500

In Bio-informatics based genome sequencing and predicting metabolic pathways research jobs I used Matlab, SAS, SPSS, R and several Bioconductor packages. Matlab had a lot of powerful tools and was easy to use, whereas SPSS is for non-programmers and R need programming skills. I am wondering what other people think is best? or there might not be one specific language but a few that lend themselves best to Bio-informatics work that is math heavy and deals with a large amount of data.

Smyth Lab

Sun, 14 Jul 2013 12:26:18 -0500

Statistical functional genomics in experimental medicine
The genome projects and the accelerated development of high-throughput genomic technologies such as microarrays have revolutionised biology. Making the most of this revolution requires the marriage of researchers from mathematical and biological backgrounds.

Research Area:
Linear models for microarray data
Digital gene expression technologies
Detection of molecular pathways
Bioinformatics resources for medical research

Link @ http://www.wehi.edu.au/faculty_members/professor_gordon_smyth/

Livestock Functional Genomics Summer School (LFG 2013)

Fri, 02 Aug 2013 09:57:37 -0500

*Livestock Functional Genomics Summer School - Call for applications*

1st Livestock Functional Genomics Summer School (LFG 2013).

This School was designed for graduate students and early-stage researchers with interest in livestock genomics, who are engaged in projects that require knowledge in the field of computational biology.

Sixty selected participants will spend 13 days receiving theoretical and practical training in genomic data handling from internationally renowned experts.

After the course, the participant should understand the basis and the context of livestock big molecular data, and be able to manipulate high density genotypes, whole genome sequences and transcriptome data.

The Summer School will be held in Araçatuba-SP Brazil, from the 13th to the 21st of September 2013.

All accepted participants will have *expenses fully covered (air ticket, hotel and meals)*, including a free pass to the 5th International Symposium on Animal Functional Genomics http://www.isafg2013.org.br

Applicants will be selected based on their résumés. Application date is due by August 10th. Results will be announced in August 12th.

Please consult website: http://www.sciencesatellite.org.br/sschool

The Human Genome Project Video 3D Animation Introduction Low)

Sat, 24 Aug 2013 19:01:19 -0500

Genome2014

Tue, 15 Oct 2013 12:47:32 -0500

Genomics has profoundly changed our way of conducting research in microbiology. The power of high–throughput DNA sequencing technologies, in particular the recent development of next generation sequencing allows researchers now to address an increasingly diverse range of biological problems. The scale and efficiency of sequence-based analyses that can now be achieved is providing unprecedented progress in diverse areas that range from the analyses of genomes to related disciplines such as transcriptional profiling - or protein - nucleic acid interaction studies: Population and metagenomics studies can now be conducted in an unprecedented large scale, regulatory processes can be studied genome-wide under hundreds of different conditions. The genome wide study of the interaction of DNA or RNA with proteins brings completely new insight into regulatory processes and even single cell analyses become now possible. The many diverse applications of next–generation sequencing and the importance of the insights that are being gained through these methods are very exiting and challenging. It is the perfect time to come together and exchange new knowledge and technologies in this area.

Thus the conference on "Microbiology after the genomics revolution - Genomes 2014" will be an appropriate and timely occasion to offer an outstanding discussion forum for the best international researchers in all fields of cutting edge microbiology research to discuss newly discovered aspects of microbiology.

More @ http://www.genomes-2014.org/