Following are the genome assembly tools based on string graph:

1.SGA (String Graph Assembler) https://github.com/jts/sga

Assembles large genomes from high coverage short read data. SGA is designed as a modular set of programs, which are used to form an assembly pipeline. SGA implements a set of assembly algorithms based on the FM-index. As the FM-index is a compressed data structure, the algorithms are very memory efficient. The SGA assembly has three distinct phases. The first phase corrects base calling errors in the reads. The second phase assembles contigs from the corrected reads. The third phase uses paired end and/or mate pair data to build scaffolds from the contigs. The output of this software is a PDF report that allows the properties of the genome and data quality to be visually explored. By providing more information to the user at the start of an assembly project, this software will help increase awareness of the factors that make a given assembly easy or difficult, assist in the selection of software and parameters and help to troubleshoot an assembly if it runs into problems.

2. SAGE: String-overlap Assembly of GEnomes https://github.com/lucian-ilie/SAGE2

SAGE, for de novo genome assembly. As opposed to most assemblers, which are de Bruijn graph based, SAGE uses the string-overlap graph. SAGE builds upon great existing work on string-overlap graph and maximum likelihood assembly, bringing an important number of new ideas, such as the efficient computation of the transitive reduction of the string overlap graph, the use of (generalized) edge multiplicity statistics for more accurate estimation of read copy counts, and the improved use of mate pairs and min-cost flow for supporting edge merging. The assemblies produced by SAGE for several short and medium-size genomes compared favourably with those of existing leading assemblers.

3. FSG: Fast String Graph

The new integrated assembler has been assessed on a standard benchmark, showing that fast string graph (FSG) is significantly faster than SGA while maintaining a moderate use of main memory, and showing practical advantages in running FSG on multiple threads. Moreover, we have studied the effect of coverage rates on the running times.

4.  BASE https://github.com/dhlbh/BASE

It enhances the classic seed-extension approach by indexing the reads efficiently to generate adaptive seeds that have high probability to appear uniquely in the genome. Such seeds form the basis for BASE to build extension trees and then to use reverse validation to remove the branches based on read coverage and paired-end information, resulting in high-quality consensus sequences of reads sharing the seeds. Such consensus sequences are then extended to contigs. BASE is a practically efficient tool for constructing contig, with significant improvement in quality for long NGS reads. It is relatively easy to extend BASE to include scaffolding.

5. Fermi https://github.com/lh3/fermi/

Fermi is a de novo assembler with a particular focus on assembling Illumina short sequence reads from a mammal-sized genome. In addition to the role of a typical assembler, fermi also aims to preserve heterozygotes which are often collapsed by other assemblers. Its ultimate goal is to find a minimal set of unitigs to represent all the information in raw reads.

If you want to learn about String Graph assembler, please read the following papers -

i) The Fragment Assembly String Graph - E. W. Myers

This paper describes the String Graph concept.

ii) Efficient construction of an assembly string graph using the FM-index - Jared T. Simpson and Richard Durbin

This earlier paper from Simpson and Durbin

iii) Efficient de novo assembly of large genomes using compressed data structures - Jared T. Simpson and Richard Durbin

Gene expression and protein expression patterns between normal and non-normal tissues is a growing area of research that may lead to the identification of candidate genes for understanding the etiology of common, complex diseases.

Lab homepage @ http://ritchielab.psu.edu/ritchielab/

./wtdbg2 -x rs -g 4.6m -t 16 -i reads.fa.gz -fo prefix
./wtpoa-cns -t 16 -i prefix.ctg.lay.gz -fo prefix.ctg.fa

Address of the bookmark: https://github.com/ruanjue/wtdbg2

Essential requirements: Experience of using bioinformatics tools.

Experience of working in Linux. Basic knowledge of computer network administration.

Desirable: Knowledge of Linux installation/administration and proficiency in either of the following:

Shell/PERL/Java/Python/VB/Oracle/MySQL/C/CUDA.

Qualification: PhD. or First class M.Sc degree in Bioinformatics or Biotechnology/life science with specialization in Bioinformatics.

Fellowships: Rs 22,000/- with HRA for PhD qualified, Rs 16000/- with HRA for NET/BET/BINC/GATE qualified and 12000/- with HRA for non NET qualified applicants.

Interested candidates may send their complete biodata along with a write-up of their experience and suitability for the position to Dr. Dinesh Gupta by email only to dinesh@icgeb.res.in within 15 days of publication of this advertisement. Kindly mark the email with subject “Application for BIF-RA-2013”

Closing date for applications: 18 October 2013

Only short listed candidates will be invited for an interview at ICGEB.

No TA/DA will be paid for attending the interview.

Advertisement: http://www.icgeb.org/tl_files/Vacancies/BIF-RA-Advt.pdf

Applications on plain paper along with details of CV (relevant photocopies of their
qualifications/experience and reprints of published work to be attached) are invited from qualified candidates for Research Fellowship in CSIR- sponsored research project.

JRF/SRF/RA (one vacancy)

CSIR sponsored “In silico design, identification and in vitro validation of lead molecule inhibitors to Bcr-Abl kinase”

JRF: M.Sc in Chemistry/ Bioinformatics/ Biotechnology with I division and NET or GATE qualified

SRF: M.Sc in chemistry/ Bioinformatics/ Biotechnology with at least two years of post- M.Sc research experience as evidenced from published papers in standard refereed journals in relevant area

RA: PhD in chemistry/ Bioinformatics/ Biotechnology with research experience in
relevant area.

As per CSIR guidelines

Notes:
1) You may visit the University of Hyderabad website www.uohyd.ernet.in to learn more about the University of Hyderabad.
2) Applicants should note that the appointment to be made is purely temporary and there is no right for claiming for any regular appointment in the University.
3) No TA/DA will be paid for attending the interview or at the time of joining the post, if selected.
4) The application should be submitted by post/courier/in-person to the address given below on or before November 1st 2013.

Prof. Lalitha Guruprasad
W-103, Gurbakhsh Singh Building
School of Chemistry
University of Hyderabad
Hyderabad- 500 046
5) Short-listed candidates will be called for interview at a short notice.

Advertisement: http://www.uohyd.ac.in/images/recruitment/chemisry_advt_101013.pdf

Address of the bookmark: https://github.com/codialab/GFAffix

Available immediately until 30th November 2015, to work on the development of bioinformatics approaches to aid analysis of data derived from the metabolomic profiling of biological matrices. The successful applicant will lead research activities on an FP7 funded EU-wide collaborative project aimed at establishing biomarker-based strategies for high throughput diagnostic screening. Key tasks will involve multivariate analysis of large datasets, bioinformatic-based selection and validation of identified markers, construction of metabolomic spectral profile databases and development of machine learning/database searching approaches amenable to analytical screening techniques. This position will offer the opportunity to travel and undertake work with project collaborators based in the Republic of Ireland and Europe.

Informal enquiries may be directed to Dr Terry McGrath, email: terry.mcgrath@qub.ac.uk.

Anticipated interview date: Thursday 31st October 2013
Salary scale: £30,424 – £39,649 per annum (including contribution points)
Closing date: Monday 21st October 2013

Telephone (028) 90973044 FAX: (028) 90971040 or e-mail on personnel@qub.ac.uk

The University is committed to equality of opportunity and to selection on merit. It therefore welcomes applications from all sections of society and particularly welcomes applications from people with a disability.

Fixed term contract posts are available for the stated period in the first instance but in particular circumstances may be renewed or made permanent subject to availability of funding.

More @ https://hrwebapp.qub.ac.uk/tlive_webrecruitment/wrd/run/ETREC107GF.open?VACANCY_ID=5616943npO&WVID=6273090Lgx&LANG=USA

Following are the list of standalone applications for network analysis:

Arena 3D

3D visualization of multi-layer networks

http://www.arena3d.org

Biana

Data integration and network management

http://sbi.imim.es/web/BIANA.php

BioLayout Express 3D 

2D/3D network visualization

http://www.biolayout.org/

BiologicalNetworks 

Efficient integrated multi-level analysis of microarray, sequence, regulatory and other data

http://www.biologicalnetworks.org

BioMiner

Modeling, analyzing and visualizing biochemical pathways and networks

http://www.zbi.uni-saarland.de/chair/projects/BioMiner

Cell Illustrator 

Petri nets for modeling and simulating biological networks

http://www.cellillustrator.com

COPASI

Analysis of biochemical networks and their dynamics

http://www.copasi.org/

Cytoscape 

Network visualization and analysis. Over 200 plugins [60]

http://www.cytoscape.org/

Dizzy

Chemical kinetics stochastic simulation software

http://magnet.systemsbiology.net/software/Dizzy/

DyCoNet

Gephi plugin that can be used to identify dynamic communities in networks

https://github.com/juliemkauffman/DyCoNet

GENeVis 

Network and pathway visualization

http://tinyurl.com/genevis/

GEPHI 

Interactive visualization and exploration for any network and complex system, dynamic and hierarchical graph.

https://gephi.org

Igraph

Collection of network analysis tools with the emphasis on efficiency, portability and ease of use

http://igraph.sourceforge.net

Medusa

Semantic and multi-edged simple networks

https://sites.google.com/site/medusa3visualization/

NAViGaTOR

Visualizing and analyzing protein-protein interaction networks

http://tinyurl.com/navigator1/

N-Browse

Interactive graphical browser for biological networks

http://www.gnetbrowse.org/

NeAT

Topological and clustering analysis of networks

http://rsat.ulb.ac.be/neat/

Ondex 

Data integration and visualization of large networks

http://www.ondex.org/

Osprey

Visualization and annotation of biological networks

http://biodata.mshri.on.ca/osprey/servlet/Index

Pajek 

Analysis and visualization of large networks and social network analysis

http://vlado.fmf.uni-lj.si/pub/networks/pajek/

PathwayAssist 

Navigation and analysis of biological pathways, gene regulation networks and protein interaction maps.

http://www.ariadnegenomics.com/downloads/

PIVOT 

Layout algorithms for visualizing protein interactions and families

http://acgt.cs.tau.ac.il/pivot/

ProCope 

Prediction and evaluation of protein complexes from purification data experiments

http://www.bio.ifi.lmu.de/Complexes/ProCope/

ProViz 

Visualization and exploration of interaction networks. Gene Ontology and PSI-MI formats supported

http://cbi.labri.fr/eng/proviz.htm

SpectralNET 

Network analysis and visualizations. Scatter plots and dimensionality reduction algorithms

https://www.broadinstitute.org/software/spectralnet

Tulip 

Enables the development of algorithms, visual encodings, interaction techniques, data models and domain-specific visualizations

http://tulip.labri.fr/TulipDrupal/

VANESA 

Automatic reconstruction and analysis of biological networks and Petri nets based on life-science database information

http://agbi.techfak.uni-bielefeld.de/vanesa/

VANTED 

Network reconstruction, data visualization, integration of various data types, network simulation

http://tinyurl.com/vanted/

yEd

Creation of diagrams manually and import external data

http://tinyurl.com/yEdGraph/

Web tools for network analysis

APID 

Unified protein-protein interactions from BIND, BioGRID, DIP, HPRD, IntAct and MINT

http://bioinfow.dep.usal.es/apid/

Arcadia 

Translates text-based descriptions of biological networks (SBML files) into standardized diagrams (Systems Biology Graphical Notation Process Description maps)

http://arcadiapathways.sourceforge.net/

AVIS 

Viewer for signaling networks

http://actin.pharm.mssm.edu/AVIS2

bioPIXIE 

Discovery of biological networks from diverse functional genomic data

http://pixie.princeton.edu/pixie

CellPublisher

Interactive representations of biochemical processes

http://cellpublisher.gobics.de/

Graphle

Distributed network exploration and visualization of interactive large, dense graphs

http://tinyurl.com/graphle/

GraphWeb 

Web server for graph-based analysis of biological networks

http://biit.cs.ut.ee/graphweb/

Hubba

Web-based service to explore the essential nodes in a network

http://hub.iis.sinica.edu.tw/Hubba

NetworkBLAST 

Analysis of protein interaction networks across species to infer protein complexes that are conserved in evolution

http://www.cs.tau.ac.il/~bnet/networkblast.htm

Pathview 

Tool set for pathway-based data integration and visualization

http://Pathview.r-forge.r-project.org/

PINA 

Integrated platform for protein interaction network construction, filtering, analysis, visualization and management

http://cbg.garvan.unsw.edu.au/pina/home.do

ReMatch 

Web-based tool for integration of user-given stoichiometric metabolic models into a database collected from public data sources

http://www.cs.helsinki.fi/group/sysfys/software/rematch/

SNOW 

Gene mapping on a reference or human protein-protein interaction network that SNOW hosts

http://snow.bioinfo.cipf.es

STITCH 

Resource to explore known and predicted interactions of chemicals and proteins

http://stitch.embl.de/

STRING

Protein interaction networks and integration of data such as genomic context, high-throughput experiments, conserved coexpression and previous knowledge derived from the literature

http://string-db.org

TVNViewer 

An interactive visualization tool for exploring networks that change over time or space

http://www.sailing.cs.cmu.edu/main/?page_id=545

tYNA 

System for managing, comparing and mining multiple networks

http://tyna.gersteinlab.org/tyna/

VisANT 

Visualization, mining, analysis and modeling of biological networks, metabolic networks and ecosystems

http://visant.bu.edu/

(INDIAN COUNCIL OF MEDICAL RESEARCH)

P.O BOX 101,
Dr. M. Miyazaki Marg,
Tajganj, Agra - 282001

Applications are invited for a walk-in interview to be held in the Seminar Hall of the on 15th November, 2013, 9:30 am for temporary positions of JRF, Lab Technician and Field attendant in a ICMR funded project entitled "Elucidating the strain differentiation and transmission dynamics of M. leprae through simple sequence repeats ISSR-PCR marker"

1. JRF (one Post)

Essential qualification: Candidates with M.Sc/IVI.Tech or equivalent degree in any life science related subjects with UGC-CSIR/ICMR/DBT-Net qualified

Desirable qualification: Experience in Molecular Biology/Computational Biology will be preferred.

Age. Maximum 28 years as on 11.11.2013. Age relaxation as per GOI rules.

Emoluments: Rs. 6,000 + 20% HRA per Month

2. Lab Technician (One Post)

Essential Qualification: 12th with DMLT/B.SCA4.SC in Life sciences

Desirable qualification: Experience in Molecular Biology/Computational Biology will be preferred.

Age: Maximum 30 years as on 11.11.2013. Age relaxation as per GOI rules.

Emoluments: Rs13,760/ Per Month

3. Field Attendant (One Post)

Essential Qualification: 10th Pass

Desirable Qualification: Experience in field work

Age: Maximum 28 years as on 11.11.2013. Age relaxation as per GOI rules.

Emoluments: Rsl2,040l Per Month

Terms: posts are purely temporary. Appointment will be initially made for a period of one (01) year and may be extended further based on the performance of the candidate up to completion of the project.

Application & Selection procedure: candidates have to appear in the walk-in-interview in person along with an application/CV on plain paper giving details of at educational qualificationq experience and submit photocopies of relevant documents at the time of interview. Selection will be based on the performance of the candidate in the interview' Candidates will not be sent any interview call letter separately. No TA/DA will be paid to the candidate for appearing in the interview. selection is not possible without appearing in the interview. All candidates must report by 9:00am on the date of interview. Advance copy of CV may be sent to m.sarathipartha@gmail.com

Advertisement: http://www.jalma-icmr.org.in/P_S_M_advertisment.pdf

• recovering signals in networks after a stimulation (cascade network reverse engineering),
• analysing periodic signals.

Address of the bookmark: https://github.com/fbertran/Patterns