C Chiang, R M Layer, G G Faust, M R Lindberg, D B Rose, E P Garrison, G T Marth, A R Quinlan, and I M Hall. SpeedSeq: ultra-fast personal genome analysis and interpretation. Nat Meth (2015). doi:10.1038/nmeth.3505.

http://www.nature.com/nmeth/journal/vaop/ncurrent/full/nmeth.3505.html

Address of the bookmark: https://github.com/hall-lab/speedseq

Please bookmarks your favourate biostatistics books in commend sectons ...

Address of the bookmark: http://www.cos.ufrj.br/~bioestatistica/livros/Introduction%20to%20Biostatistics.pdf

GoJS offers many advanced features for user interactivity such as drag-and-drop, copy-and-paste, in-place text editing, tooltips, context menus, automatic layouts, templates, data binding and models, transactional state and undo management, palettes, overviews, event handlers, commands, and an extensible tool system for custom operations.

GoJS is pure JavaScript, so users get interactivity without requiring round-trips to servers and without plugins. GoJS normally runs completely in the browser, rendering to an HTML5 Canvas element or SVG without any server-side requirements. GoJS does not depend on any JavaScript libraries or frameworks, so it should work with any HTML or JavaScript framework or with no framework at all.          

More at http://gojs.net/latest/index.html

Address of the bookmark: http://gojs.net/latest/index.html

FSA brings the high accuracies previously available only for small-scale analyses of proteins or RNAs to large-scale problems such as aligning thousands of sequences or megabase-long sequences. FSA introduces several novel methods for constructing better alignments:

• FSA uses machine-learning techniques to estimate gap and substitution parameters on the fly for each set of input sequences. This "query-specific learning" alignment method makes FSA very robust: it can produce superior alignments of sets of homologous sequences which are subject to very different evolutionary constraints.
• FSA is capable of aligning hundreds or even thousands of sequences using a randomized inference algorithm to reduce the computational cost of multiple alignment. This randomized inference can be over ten times faster than a direct approach with little loss of accuracy.
• FSA can quickly align very long sequences using the "anchor annealing" technique for resolving anchors and projecting them with transitive anchoring. It then stitches together the alignment between the anchors using the methods described above.
• The included GUI, MAD (Multiple Alignment Display), can display the intermediate alignments produced by FSA, where each character is colored according to the probability that it is correctly aligned (see the picture and movie at the top of the page).

You can see more information on the FAQ. 

Address of the bookmark: http://fsa.sourceforge.net/

More at http://sequenceserver.com.

Address of the bookmark: https://github.com/wurmlab/sequenceserver

https://www.ncbi.nlm.nih.gov/research/groups/koonin/

#rasalsi #rasa In our Industrial program you will get Knowledge on RNA Seq, CHIP Seq,

Batch Starts From 18^th November 2019

#hurryup #registernow #enquirenow The primary goal of the industrial training program is to provide students with necessary skills making with employable. RASA LSI trains students with the enhanced skills required for them to excel in jobs in biotechnology, pharmaceuticals, BioIT and related industry sectors. At Rasa you will  learn from industry leaders how to apply these skills in life science & have a command over software developing process  by using various methodologies. For Registration visit us on: https://www.rasalsi.com/index.php/front-page/industrial-training/

https://github.com/zhangzhwlab/delta

Address of the bookmark: https://github.com/zhangzhwlab/delta

Requirements
Doctoral degree in Bioinformatics, Computational Biology, (Bio)physics/-mathematics, Biochemistry/Biology or similar with strong quantitative and numeric focus
Ability to numerically process complex and large data sets
Good programming skills (R/Bioconductor and/or Python preferred, Linux is a plus)
Experience in analyzing next-generation sequencing data sets using network biology
Scientific publication record in applied bioinformatics
Familiarity with single cell NGS analyses and other –omics techniques is a plus, but not essential

1. Supply your genes/genomic segments/phylogenetic tree of interest in the input-box by
   • selecting the type of identifier and pasting identifiers (one per line)
   • or by using the gene ID search tool
   • or with the BLAST search tool
2. Click "Visualize context".

Consult the documentation to learn more about MGcV.

Address of the bookmark: http://mgcv.cmbi.ru.nl/