BOL: Related items

Largest Genome Sequenced

Rahul Agarwal — Fri, 21 Mar 2014 13:57:19 -0500

The enormous size of the loblolly pine genome having 22 billion base pairs compared to only 3 billion in the human genome. In other words, it is seven times larger than a human’s and also the largest and the most complete conifer genome ever sequenced.

Related Paper:

http://genomebiology.com/2014/15/3/R59/abstract

Address of the bookmark: http://www.news.ucdavis.edu/search/news_detail.lasso?id=10859

New RNA Seq tool

Rahul Agarwal — Fri, 25 Apr 2014 10:59:04 -0500

"By removing the time-consuming step of read mapping, the authors reported, Sailfish able to provide quantification estimates 20–30 times faster than current methods without loss of accuracy."

Tool link:

http://www.cs.cmu.edu/~ckingsf/software/sailfish/

Address of the bookmark: http://www.genengnews.com/gen-news-highlights/lightweight-algorithms-sail-through-rna-sequencing-data/81249765/

GenXPro GmbH

Rahul Agarwal — Thu, 22 May 2014 07:18:35 -0500

GenXPro GMbH is service provider for entire spectrum of nucleotide-based information of any biological sample. By combining intelligent data reduction techniques and latest next generation sequencing technologies, our service portfolio provides most accurate and cost efficient solutions for transcriptomic-, genomic- or epigenomic research.

GENXPRO GMBH, ALTENHÖFERALLEE 3, 60438 FRANKFURT MAIN, GERMANY

Website: http://www.genxpro.info/products_and_services/

PHONE: +49 (0)69- 95 73 97 10, FAX: +49 (0)69- 95 73 97 06

EMAIL: info@genxpro.de

The Genome 10K Project

Tue, 29 Jul 2014 09:11:04 -0500

https://genome10k.soe.ucsc.edu The Genome 10K project aims to assemble a genomic zoo—a collection of DNA sequences representing the genomes of 10,000 vertebrate species, approximately one for every vertebrate genus. The trajectory of cost reduction in DNA sequencing suggests that this project will be feasible within a few years. Capturing the genetic diversity of vertebrate species would create an unprecedented resource for the life sciences and for worldwide conservation efforts. The growing Genome 10K Community of Scientists (G10KCOS), made up of leading scientists representing major zoos, museums, research centers, and universities around the world, is dedicated to coordinating efforts in tissue specimen collection that will lay the groundwork for a large-scale sequencing and analysis project.

GraphMap - A highly sensitive and accurate mapper for long, error-prone reads

Rahul Agarwal — Mon, 06 Jul 2015 08:46:53 -0500

GraphMap is a novel mapper targeted at aligning long, error-prone third-generation sequencing data.
It is designed to handle Oxford Nanopore MinION 1d and 2d reads with very high sensitivity and accuracy, and also presents a significant improvement over the state-of-the-art for PacBio read mappers.

GraphMap was also designed for ease-of-use: the default parameters can handle a wide range of read lengths and error profiles, including: Illumina, PacBio and Oxford Nanopore.
This is an especially important feature for technologies where the error rates and error profiles can vary widely across, or even within, sequencing runs.

http://biorxiv.org/content/early/2015/06/10/020719

Address of the bookmark: https://github.com/isovic/graphmap

GRASS: a generic algorithm for scaffolding next-generation sequencing assemblies.

Abhimanyu Singh — Tue, 23 May 2017 05:20:32 -0500

GRASS (GeneRic ASsembly Scaffolder)-a novel algorithm for scaffolding second-generation sequencing assemblies capable of using diverse information sources. GRASS offers a mixed-integer programming formulation of the contig scaffolding problem, which combines contig order, distance and orientation in a single optimization objective. The resulting optimization problem is solved using an expectation-maximization procedure and an unconstrained binary quadratic programming approximation of the original problem. We compared GRASS with existing HTS scaffolders using Illumina paired reads of three bacterial genomes. Our algorithm constructs a comparable number of scaffolds, but makes fewer errors. This result is further improved when additional data, in the form of related genome sequences, are used.

Address of the bookmark: https://github.com/AlexeyG/GRASS

Earth BioGenome Project

Jit — Wed, 25 Apr 2018 07:48:56 -0500

The central goal of the Earth BioGenome Project is to understand the evolution and organization of life on our planet by sequencing and functionally annotating the genomes of 1.5 million known species of eukaryotes, a massive group that includes plants, animals, fungi and other organisms whose cells have a nucleus that houses their chromosomal DNA. To date, the genomes of less than 0.2 percent of eukaryotic species have been sequenced.

More at https://www.ucdavis.edu/news/earth-biogenome-project-aims-sequence-dna-all-complex-life

Choosing the Right NGS Sequencing Instrument for Your Study

Neel — Wed, 15 Jun 2022 00:37:29 -0500

The right sequencing instrument for your study depends on your project goal. Setting aside turnaround time and price, it essentially comes down to the numbers of reads and read length you need for your experiment. Below, we've described and compared metrics for each of the instruments available. If you’re new to high-throughput sequencing and have questions about how you should design your sequencing run, fill out our free consultation form and we'll get in touch with you to help.

More at https://genohub.com/ngs-instrument-guide/

Address of the bookmark: https://genohub.com/ngs-instrument-guide/

Compressive Genomics

Rahul Agarwal — Sun, 11 Aug 2013 11:13:58 -0500

The key to finding a solution is to notice that most genomicsequences differ by very little. It may well be that the number of complete genome sequences being stored is increasing rapidly, but the actual amount of new data is very small. In other words, a single DNA sequence isn't particularly compressible but a set of sequences shares so much in common that the redundancy can be used to store them in a much smaller storage space. (Source:e-article from Alex Armstrong)

http://www.i-programmer.info/news/181-algorithms/4537-a-new-dna-sequence-search-compressive-genomics.html

http://en.wikipedia.org/wiki/Compression_of_Genomic_Re-Sequencing_Data

http://www.nature.com/nbt/journal/v30/n7/full/nbt.2241.html

http://bioinformatics.oxfordjournals.org/content/29/13/i283.full

http://groups.csail.mit.edu/cb/cast/

Precision Medicine

Rahul Agarwal — Sat, 24 Aug 2013 15:47:03 -0500

Coupling established clinical–pathological indexes with state-of-the-art molecular profiling to create diagnostic, prognostic, and therapeutic strategies precisely tailored to each patient's requirements — hence the term “Precision medicine”

Source:http://www.nejm.org/doi/full/10.1056/NEJMp1114866

Another video on precision medicine:

http://www.youtube.com/watch?v=Pi8W0yOXnzE

Precision Medicine basically intergrates bioinformatics, genomics , genetics, molecular biology and nanotechnology to deliver precise cure/diagnotics to a specific patient.

Examples:

The drug imatinib (Gleevec) designed to inhibit an altered enzyme produced by a fused version of two genes found in chronic myelogenous leukemia.
The breast cancer drug trastuzumab (Herceptin) works only for women whose tumors have a particular genetic profile called HER-2 positive.

E.g. source :

http://www.bionews-tx.com/news/2013/08/15/how-the-impact-of-cancer-genomics-on-precision-medicine-is-revolutionizing-cancer-treatment/

Address of the bookmark: http://www.cbsnews.com/video/watch/?id=50149783n