• Updated human gene set (GENCODE 21)
• Updated rat gene set including manual annotation from HAVANA
• New species: Vervet-African green monkey
• Imported Transcript Support Levels (TSLs) from UCSC for human and mouse
• Imported APPRIS flag for human and mouse
• Updated Amazon molly gene set

Find more at http://www.ensembl.info/blog/2014/10/02/ensembl-77-has-been-released/

Address of the bookmark: https://github.com/knausb/vcfR

Orange Bioinformatics provides access to publicly available data, like GEO data sets, Biomart, GO, KEGG, Atlas, ArrayExpress, and PIPAx database. As for the analytics, there is gene selection, quality control, scoring distances between experiments with multiple factors. All features can be combined with powerful visualization, network exploration and data mining techniques from the Orange data mining framework.

Address of the bookmark: https://pypi.python.org/pypi/Orange-Bioinformatics/2.5.34

CPAT - https://github.com/liguowang/cpat, http://lilab.research.bcm.edu/ (web server)

CPC2 - https://github.com/gao-lab/CPC2_standalone, http://cpc2.gao-lab.org/ (web server)

Infernal - http://eddylab.org/infernal/, https://github.com/EddyRivasLab/infernal

NCBI RefSeq - https://www.ncbi.nlm.nih.gov/refseq/

Rfam - http://rfam.xfam.org/, https://docs.rfam.org/en/latest/index.html

SILVA - https://www.arb-silva.de/

RNAmmer - http://www.cbs.dtu.dk/services/RNAmmer/ (web server, standalone download link)

Qualified and interested candidates can send their curriculum vitae by e-mail to hr@drils.org on or before 27th October 2014 mention in the subject line of the mail the following code: AMPK-Biology.

Selected candidates will be called for a personal interview to Dr. Reddy’s Institute of Life Sciences, University of Hyderabad Campus, Gachibowli, Hyderabad. The selected candidate is expected to report within two weeks from the date of selection to start work on the project.

Junior Research Fellowship (Molecular Modeling/Biology) for two years and Senior Research fellowship for one year

Junior Research Fellowship: Rs. 15,600/- (consolidated) per month for first two years.
Senior Research Fellowship: Rs. 18,200/-(consolidated) per month for the 3rd year.

Duration: The duration of the fellowship is for three years. However, the performance of the candidate will be reviewed after the completion of every year and the fellowship will be renewed only upon satisfactory performance.

Responsibilities:

1) Literature search.
2) Design, plan and execute experiments under the supervision of the scientist.
3) Provide scientific support to the scientist in his/her research activities.
4) Book keeping and maintenance of stocks and consumables.

Essential Qualifications:

Required: M.Sc. in Microbiology/Biotechnology/Bioinformatics or any other related branch of basic Sciences from a recognized university/institute with a consistent academic record of minimum 60% aggregate in all qualifying examinations. The candidate should be NET qualified for lectureship. The candidate should be motivated to work with dedication.

Desirable: expertise/experience in both Molecular Modeling and Molecular Biology.

Experience: 0-2 years in the areas of Molecular Modeling and/or Molecular Biology and cell biology and Biochemistry.

Preferable: Relevant research experience as evident from thesis/dissertation/project work.

Advertisement: http://www.ilsresearch.org/userfiles/Junior%20REsearch%20Fellowship%20-%20AMPK(Biology).pdf

• BigDataScript – A cross-system scripting language for working with big data pipelines in computer systems of different sizes and capabilities. [ paper-2014 | web ]
• Bpipe – A small language for defining pipeline stages and linking them together to make pipelines. [ web ]
• Common Workflow Language – a specification for describing analysis workflows and tools that are portable and scalable across a variety of software and hardware environments, from workstations to cluster, cloud, and high performance computing (HPC) environments. [ web ]
• Cromwell – A Workflow Management System geared towards scientific workflows. [ web ]
• Galaxy – a popular open-source, web-based platform for data intensive biomedical research. Has several features, from data analysis to workflow management to visualization tools. [ paper-2018 | web ]
• Nextflow (recommended) – A fluent DSL modelled around the UNIX pipe concept, that simplifies writing parallel and scalable pipelines in a portable manner. [ paper-2018 | web ]
• Ruffus – Computation Pipeline library for python widely used in science and bioinformatics. [ paper-2010 | web ]
• SeqWare – Hadoop Oozie-based workflow system focused on genomics data analysis in cloud environments. [ paper-2010 | web ]
• Snakemake – A workflow management system in Python that aims to reduce the complexity of creating workflows by providing a fast and comfortable execution environment. [ paper-2018 | web ]
• Workflow Descriptor Language – Workflow standard developed by the Broad. [ web ]

Responsibilities

Lead teams of scientists in structuring, prototyping, and executing large-scale bioinformatic and other analysis.
Develop novel bioinformatics, statistical, data processing, pathway, data mining and other algorithms to identify biological signals and their clinical correlates in broad kinds of individual and population data.
Develop novel platform-level analytical tools for sequence-based assays (assembly, annotation, variant calling and interpretation, phasing, genome structure, etc.), expression assays (RNAseq and microarray), proteomics, and metabolomics.
Develop statistical models that robustly correlate complex laboratory-derived information with phenotypic and clinical information.
Create scientifically rigorous visualizations, communications, and presentations of results.

Reference @ https://www.google.com/about/careers/search#!t=jo&jid=62095001

This package is a loose collection of scripts. To run the correction
routine see the section below. Descriptions of the other scripts
are at the bottom of this file.

Contact: gurtowsk@cshl.edu

In short, the correction algorithm takes as input the unitigs from a short read assembly and uses them to correct long read data. More background information for the algorithm can be found:
http://schatzlab.cshl.edu/presentations/2013-06-18.PBUserMeeting.pdf

Address of the bookmark: https://github.com/jgurtowski/ectools

Faculty Positions
The Central University of Punjab (CUP), Bathinda will be having the Schools and Departments as given in Table-I. The University invites applications from eligible candidates for the posts of Professors (Pay Band Rs. 37400-67000 with AGP of Rs. 10, 000/-), Associate Professors (Pay Band Rs.37400-67000 with AGP of Rs. 9,000/-) and Assistant Professors (Pay Band Rs.15600-39100 with AGP of Rs. 6,000/-)

POSITION AVAILABLE IN THE AREA OF SPECIALIZTION

3. Bioinformatics,

Procedure to apply: Application forms along with API form complete in all respect along with necessary documents and application fee of Rs. 750/-. (Rs. 250/- for Scheduled Caste/Scheduled Tribe/Person with disabilities) should be sent to:

Registrar (Officiating)
Central University of Punjab
City Campus, Mansa Road
Bathinda-151 001

Application forms from the prospective candidates are accepted upto November 10, 2014.

Based on the qualification of the candidates and the need of the university, the applications received will be processed through appropriately constituted selection committees shortly. Minimum qualification can be relaxed in case of exceptionally outstanding candidate. For further details visit www.cup.ac.in; www.centralunipunjab.com; www.cup.edu.in

The candidate should download the application form available at website www.cup.ac.in;
www.centralunipunjab.com; and submit it complete in all respects on or before 10th November 2014.

Those who have applied earlier need to submit Academic Performance Index (API) form, 5 copies of Summary of the Application Form (available at: www.cup.ac.in; www.centralunipunjab.com and Updated CV if not updated recently (without application fee).

http://cup.edu.in/Faculty_details_and_general_instructions.pdf

http://cup.edu.in/Final%20Application%20and%20summary%20Sheet%20and%20Api%20form.pdf

Take a look at the PRICE software from the DeRisi lab. Its meant to do something very similar. http://derisilab.ucsf.edu/index.php?page=software

You could also look at SSPACE (http://www.baseclear.com/landingpages/basetools-a-wide-range-of-bioinformatics-solutions/sspacev12/), ATLAS tools (http://www.hgsc.bcm.tmc.edu/content/bcm-hgsc-software), and SCARPA (http://compbio.cs.toronto.edu/hapsembler/scarpa.html).

See the PAGIT protocol: http://www.sanger.ac.uk/resources/software/pagit/

In particular, take a look at the IMAGE tool: http://genomebiology.com/2010/11/4/R41

Also SOAPdenovo has ha function for scaffolding. Not sure about ABYSS

Here there is a useful explanation of several tools.

https://bioinformaticsonline.com/search?q=scaffolding&entity_type=object&entity_subtype=bookmarks&offset=0&search_type=entities

I could be wrong, but the above answers to your hypothetical scenario appear to miss the point that you aren't interested in assembling the full genome, just the 100 kb part you're interested in. I suggest the following algorithm:

1. Start with the initial assembly C0 of the contigs you have identified as overlapping your region of interest, and the set S of reads those contigs contain. Let C = C0.

2. Repeat:
a. Identify paired-end reads (not in C) for which one or both ends align within, or extending, contigs in C.
b. Identify unpaired reads that align extending these new paired-end reads.
c. Construct a new assembly C' from C and the new reads identified in (a) and (b).
d. Trim C' so it does not extend more than 100 kb to either end of C0. Set C = C'.
e. Let S' denote the reads that contribute to C'. If S' does not contain any reads not present in S, stop. Otherwise, Set S = S'.

3. If you don't have a complete assembly of the region of interest, generate an STS for each end of each contig, probe a library for clones including these STSes, subclone these clones into a paired-end sequencing vector, and generate paired-end reads for this library; then try steps (1) and (2) again, adding these new sequencing reads to what you had before.

4. If your average sequencing depth for the region of interest exceeds 25 or so without filling all gaps, it is likely that the remaining gaps represent sequences that are not getting cloned in your sequencing vectors. Try different sequencing vectors.