You should begin by downloading the program from here. You will need to choose the link that matches your computing platform and then follow the instructions for opening the download package.

Once you have done this, you will be ready to try some example analyses on the test data that are provided with the download. The section on Examples shows how to use the most common IMPUTE2 functions. We suggest that you work through these examples and try to understand what the elements of each command are doing. If you don't understand something or would like to know if the program can perform a function that isn't listed, you can read our FAQ or submit a question to our mail list.

When you have learned the basic functionality of the program, you can use several features of this website to prepare your own analysis:

• Learn about best practices for imputation.
• Download reference data that you can use to impute genotypes in your study.
• Look through a complete list of program options.

Address of the bookmark: https://mathgen.stats.ox.ac.uk/impute/impute_v2.html

This collection highlights important statistical issues that biologists should be aware of and provides practical advice to help them improve the rigor of their work.

Nature Methods' Points of Significance column on statistics explains many key statistical and experimental design concepts. Other resources include an online plotting tool and links to statistics guides from other publishers.

Address of the bookmark: http://www.nature.com/collections/qghhqm

Address of the bookmark: http://kobas.cbi.pku.edu.cn/

Address of the bookmark: http://www.nature.com/nature/journal/v491/n7424/abs/nature11622.html

tax_id:
the unique identifier provided by NCBI Taxonomy
for the species or strain/isolate

GeneID:
the unique identifier for a gene
ASN1: geneid

Symbol:
the default symbol for the gene
ASN1: gene->locus

LocusTag:
the LocusTag value
ASN1: gene->locus-tag

Synonyms:
bar-delimited set of unofficial symbols for the gene

dbXrefs:
bar-delimited set of identifiers in other databases
for this gene. The unit of the set is database:value.
Note that HGNC and MGI include 'HGNC' and 'MGI', respectively,
in the value part of their identifier. Consequently,
dbXrefs for these databases will appear like:
HGNC:HGNC:1100
This would be interpreted as database='HGNC', value='HGNC:1100'
Example for MGI:
MGI:MGI:104537
This would be interpreted as database='MGI', value='MGI:104537'

chromosome:
the chromosome on which this gene is placed.
for mitochondrial genomes, the value 'MT' is used.

map location:
the map location for this gene

description:
a descriptive name for this gene

type of gene:
the type assigned to the gene according to the list of options
provided in https://www.ncbi.nlm.nih.gov/IEB/ToolBox/CPP_DOC/lxr/source/src/objects/entrezgene/entrezgene.asn

Symbol from nomenclature authority:
when not '-', indicates that this symbol is from a
a nomenclature authority

Full name from nomenclature authority:
when not '-', indicates that this full name is from a
a nomenclature authority

Nomenclature status:
when not '-', indicates the status of the name from the
nomenclature authority (O for official, I for interim)

Other designations:
pipe-delimited set of some alternate descriptions that
have been assigned to a GeneID
'-' indicates none is being reported.

Modification date:
the last date a gene record was updated, in YYYYMMDD format

Feature type:
pipe-delimited set of annotated features and their classes or
controlled vocabularies, displayed as feature_type:feature_class
or feature_type:controlled_vocabulary, when appropriate; derived
from select feature annotations on RefSeq(s) associated with the
GeneID

Address of the bookmark: ftp://ftp.ncbi.nih.gov/gene/DATA/GENE_INFO/

Post Research Officer, NTRF, Kolkata

Essential Post Graduate degree in Life Science having special paper in Bioinformatics. Post Graduate degree in Bioinformatics.

Desirable Ph. D. in the area of computational biology or bioinformatics.

Job Experience Work experience on database development, capable to work independently and efficient in bioinformatics related project.

Job Responsibility

To develop database on various aspects of tea research.

Screening of the In-house projects of NTRF at the preliminary level.

Review and evaluation of In-house projects of NTRF. Technical monitoring of the In-house projects of NTRF.

Reviewing the final technical report of the In-house projects of NTRF.

Putting-up of same proposals for taking approval and sanction of the competent authority.

Physical and technical verification of the In-house projects of NTRF.

To assist in organizing seminars / workshops / meetings etc.

Interested candidate may appear for walk-in Interview on 17 th November, 2016

More Info :

http://www.teaboard.gov.in/pdf/Recruitment_for_the_post_of_Research_Officer_pdf7538.pdf

Address of the bookmark: https://genomebiology.biomedcentral.com/articles/10.1186/gb-2002-3-12-research0082

Address of the bookmark: http://augustus.gobics.de/binaries/scripts/

PANNZER (Protein ANNotation with Z-scoRE) is a fully automated service for functional annotation of prokaryotic and eukaryotic proteins of unknown function. The tool is designed to predict the functional description (DE) and GO classes.

PANNZER2 processes bacterial proteomes in minutes and eukaryotic proteomes in an hour. You can use AAI-profiler to summarize a proteome's species neighbors and reveal taxonomic identity or contamination.

Address of the bookmark: http://ekhidna2.biocenter.helsinki.fi/sanspanz/#

http://compbio.cs.toronto.edu/prism/

Address of the bookmark: http://compbio.cs.toronto.edu/prism/