http://gkno.me/how-to/install.html

http://gkno.me/software.html

Address of the bookmark: http://gkno.me/

In the mid 1960's scientists discovered that many genomes contain stretches of highly repetitive DNA sequences ( see Reassociation Kinetics Experiments, and C-Value Paradox ). These sequences were later characterized and placed into five categories:

Simple Repeats - Duplications of simple sets of DNA bases (typically 1-5bp) such as A, CA, CGG etc.
Tandem Repeats - Typically found at the centromeres and telomeres of chromosomes these are duplications of more complex 100-200 base sequences.
Segmental Duplications - Large blocks of 10-300 kilobases which are that have been copied to another region of the genome.
Interspersed Repeats
Processed Pseudogenes, Retrotranscripts, SINES - Non-functional copies of RNA genes which have been reintegrated into the genome with the assitance of a reverse transcriptase.
DNA Transposons
Retrovirus Retrotransposons
Non-Retrovirus Retrotransposons ( LINES )

Currently up to 50% of the human genome is repetitive in nature and as improvements are made in detection methods this number is expected to increase.

On the other hand; In genetics, the term palindrome refers to a sequence of nucleotides along a DNA (deoxyribonucleic acid) or RNA (ribonucleic acid) strand that contains the same series of nitrogenous bases regardless from which direction the strand is analyzed. Akin to a language palindrome—wherein a word or phrase is spelled the same left-to-right as right-to-left (e.g., the word RADAR or the phrase "able was I ere I saw elba")—with genetic palindromes it does not matter whether the nucleic acid strand is read starting from the 3' (three prime) end or the 5' (five prime) end of the strand.

Recent research on palindromes centers on understanding palindrome formation during gene amplification. Other studies have attempted to relate palindrome formation to molecular mechanisms involved in double stranded breaks and in the formation of inverted repeats. Assisted by high speed computers, other groups of scientists link palindrome formation to the conservation of genetic information.

Related to the direction of transcription by RNA polymerase, DNA strands have upstream and downstream terminus defined by differing chemical groups at each end. The ends of each strand of DNA or RNA are termed the 5' (phosphate bound to the 5' position carbon) and 3' (phosphate bound to the 3' carbon) ends to indicate a polarity within the molecule. Using the letters A, T, C, G, to represent the nitrogenous bases adenine, thymine, cytosine, and guanine found in DNA, and the letters A, U, C, G to represent the nitrogenous bases adenine, uracil, cytosine, guanine found in RNA (Note that uracil in RNA replaces the thymine found in DNA), geneticists usually represent DNA by a series of base codes (e.g., 5' AATCGGATTGCA 3'). The base codes are usually arranged from the 5' end to the 3' end.

Because of specific base pairing in DNA (i.e., adenine (A) always bonds with (thymine (T) and cytosine (C) always bonds with guanine (G)) the complimentary stand to the sequence 5' AATCGGATTGCA 3' would be 3' TTAGCCTAACGT 5'.

With palindromes the sequences on the complimentary strands read the same in either direction. For example, a sequence of 5' GAATTC3' on one strand would be complimented by a 3' CTTAAG 5' strand. In either case, when either strand is read from the 5' prime end the sequence is GAATTC. Another example of a palindrome would be the sequence 5' CGAAGC 3' that, when reversed, still reads CGAAGC.

Palindromes are important sequences within nucleic acids. Often they are the site of binding for specific enzymes (e.g., restriction endobucleases) designed to cut the DNA strands at specific locations (i.e., at palindromes).

Palindromes may arise from brakeage and chromosomal inversions that form inverted repeats that compliment each other. When a palindrome results from an inversion, it is often referred to as an inverted repeat. For example, the sequence 5' CGAAGC 3', if inverted (reversed 180°), still reads CGAAGC.

The European Molecular Biology Open Software Suite (EMBOSS) includes some basic tools for finding tandem repeats and inverted repeats (see B.6.22. Applications in group Nucleic:repeats). There are many on-line services providing the EMBOSS tools, for example:

• Wageningen Bioinformatics Webportal EMBOSS explorer
• Mobyle@Pasteur
• Soaplab2 Web Services at Vital-IT

For more sophisticated repeat finding you will want to look at tools using Repbase for example:

• CENSOR
  • CENSOR@GIRI
  • CENSOR@EMBL-EBI
• RepeatMasker
• MUMmer (scan_for_match)
• Emboss Palindrome

Other nucleotide repeat finding methods found by a couple of web searches:

• Tandem Repeats Finder
• RECON
• RepeatRunner
• REPuter
• Imperfect Microsatellite Extractor (IMEx)
• Spectral Repeat Finder (SRF)
• REPFIND
• CRISPRfinder
• GrailEXP
• CONREPP
• find_palindromes
• Palindrome
• EMBOSS Palindrome
• Palindrome Search

School of Life Sciences

Department of Animal Biology

Applications are invited on a plane paper (along with copies of educational qualifications and experience) from eligible candidates for the selection of following position to work under a collaborative research project entitled “Development and application of high resolution genome conformation capture technology to investigate genome architecture in space and time” between University of Hyderabad and CR Rao advanced Institute of Mathematics, Statistics and Computer Sciences, sponsored by Department of Biotechnology, Government of India, New Delhi

Name and No. of positions JRF‐ONE

Emoluments for the position Rs. 25,000/p.m. + Eligible HRA

Qualifications MSc or M.Tech in any branch of biology/bioinformatics/computational biology/computer sciences/Mathematics/Physics

Duration Appointments are made initially for ONE year and can be extended further TWO years or until the duration of project

Our laboratory is interested in understanding signalling and spatiotemporal dynamics of 3‐Dimensional genome architecture and gene expression during embryonic stem cell differentiation by utilizing a combination of cellular, molecular genetics, Biochemical and computational tools in combination with next generation sequencing based chromatin structure analysing methods. Successful candidates shall pursue project related to either experimental or computational analysis of genome and Epigenomics data derived from human and mouse cells. Experience in Computational biology, bioinformatics, statistics, machine learning and algorithmic development is required. Knowledge of programming languages (e.g. C, C++, Perl, Python, Ruby etc.) and statistical framework (e.g. R, matlab, etc.) is preferable. Basic understanding of molecular biology will be an added advantage.

Interested candidates with the above mentioned qualification can send their curriculum vitae to Dr. K. Sreenivasulu, Department of Animal Biology, School of Life Sciences, South campus, University of Hyderabad or via email at positionssklab@gmail.com or svksl@uohyd.ernet.in.

Candidates with CSIR/UGC/ICMR/DBT/BINC qualifications if interested in above mentioned area of research are welcomed to approch principal investigator for a position leading to PhD. Last date for submission of applications is 17/06/2016. Eligible candidates will be called for an interview and they should carry all original certificates of the qualifying exam. No TA/ DA will be paid for attending the interview or at the time of joining the post.

Advertisement: http://www.uohyd.ac.in/images/recruitment/jrf_260516.pdf

More at http://www.ncbi.nlm.nih.gov/projects/HistoneDB2.0/index.fcgi/browse/

Address of the bookmark: http://www.ncbi.nlm.nih.gov/projects/HistoneDB2.0/index.fcgi/browse/

MutaBind guides you through this process, step by step, starting with selecting a protein complex and inputting PDB code or uploading PDB files. You can also retrieve results with a job ID number, view help documents, and review the MutaBind method and references.

More at http://www.ncbi.nlm.nih.gov/projects/mutabind/index.fcgi/

GAEMR’s analysis philosophy is centered on contiguity, correctness, and completeness -- how many pieces in an assembly composed of, how well those pieces accurately represent the genome sequenced, and how much of that genome is represented by those pieces. By performing over twenty different analyses based on these principles, GAEMR gives a clear picture of the condition of a genome assembly. 

Address of the bookmark: https://www.broadinstitute.org/software/gaemr/

Results: We present Cnidaria, a practical tool for clustering genomic and transcriptomic data with no limitation on ge-nome size or phylogenetic distances. We successfully simultaneously clustered 169 genomic and transcriptomic datasets from 4 kingdoms, achieving 100% accuracy at supra-species level and 78% accuracy for species level.

Availability and Implementation: Cnidaria is written in C++ and Python and is available at http://www.ab.wur.nl/cnidaria.

Contact: Saulo Aflitos - sauloal@gmail.com

Supplementary information: Supplementary data are available at Bioinformatics online.

Address of the bookmark: https://github.com/sauloal/cnidaria/wiki

Address of the bookmark: http://greengenes.lbl.gov/cgi-bin/nph-index.cgi

Title of Project : 1. “Analysis Of The Structures Of Known Antimicrobial Peptides Using Machine Learning Algoitms And Molecular Dynamics Simulations”

Senior Research Fellow /1 Post

Qualification: First class M.Sc. in Bioinformatics/ Biological Sciences from recognized university with 2 years research experience and CSIR/UGC/ICMR net qualified OR First class M.Sc. in Bioinformatics/ Biological Sciences from recognized university with 2 years research experience Research experience in bioinformatics and wetlab methods.

Age: Not exceeding 35 Years

Pay Scale : Rs.18,000/- + 30% HRA Rs.14,000/- + 30% HRA

Project Assistant (Level-II) /1 Post

Qualification: First class M.Sc. in Bioinformatics/ Biological Sciences/Computer Sciences Training experience in bioinformatics and wetlab methods .

Age: Not exceeding 28 Years

Pay Scale : Rs.8,000
How to apply
Candidates must bring along with them all the relevant documents in original and one set of attested photocopies of the same and one passport size recent colour photograph.

Walk-in-Interview on 28.06.2016 between 09:00 hrs. to 12:00 hrs.

More at http://www.nirrh.res.in/links/job_oppotunities.htm

bcftools: a set of companion tools, currently bundled with SAMtools, for identifying and filtering genomics variants.

bowtie: widely used, open source alignment software for aligning raw sequence reads to a reference genome.

BAM Format: binary, compressed format for storing SAM data.

BCF Format: Binary call format. Binary, compressed format for storing VCF data.

CIGAR String: Compact Idiosyncratic Gapped Alignment Report. A compact string that (partially) summarizes the alignment of a raw sequence read to the reference genome. Three core abbreviations are used: M for alignment match; I for insertion; and D for Deletion. For example, a CIGAR string of 5M2I63M indicates that the first 5 base pairs of the read align to the reference, followed by 2 base pairs, which are unique to the read, and not in the reference genome, followed by an additional 63 base pairs of alignment.

FASTA Format: text format for storing raw sequence data. For example, the FASTA file at: http://www.ncbi.nlm.nih.gov/nuccore/NC_008253 contains entire genome for Escherichia coli 536.

FASTQ Format: text format for storing raw sequence data along with quality scores for each base; usually generated by sequencing machines.

genotype likelihood: the probability that a specific genotype is present in the sample of interest. Genotype likelihoods are usually expressed as a Phred-scaled probability, where P = 10 ^ (-Q/10). For example, if the genotype TT (both alleles are T) at position 1,299,132 in human chromosome 12 (reference G) is 37, this translates to a probability of 10^-37/10 = 0.0001995, meaning that there is very low probability that the reads in your sample support a TT genotype. On the other hand, a genotype of AA at the same position with a score of 0 translates into a probability of 10^-0 = 1, indicating extremely high probability that your sample contains a homozygous mutation of G to A.

mate-pair: in paired-end sequencing, both ends of a single DNA or RNA fragment are sequenced, but the intermediate region is not. The two ends which are sequenced form a pair, and are frequently referred to as mate-pairs.

QNAME: unique identifier of a raw sequence read (also known as the Query Name). Used in FASTQ and SAM files.

paired-end sequencing: sequencing process where both ends of a single DNA or RNA fragment are sequenced, but the intermediate region is not. Particularly useful for identifying structural rearrangements, including gene fusions.

Phred-scaled probability: a scaled value (Q) used to compactly summarize a probability, where P = 10^-Q/10. For example, a Phred Q score of 10 translates to probability (P) = 10^-10/10 = 0.1. Phred-scaled probabilities are common in next-generation sequencing, and are used to represent multiple types of quality metrics, including quality of base calls, quality of mappings, and probabilities associated with specific genotypes. The name Phred refers to the original Phred base-calling software, which first used and developed the scale.

Phred quality score: a score assigned to each base within a sequence, quantifying the probability that the base was called incorrectly. Scores use a Phred-scaled probability metric. For example, a Phred Q score of 10 translates to P=10^-10/10 = 0.1, indicating that the base has a 0.1 probability of being incorrect. Higher Phred score correspond to higher accuracy. In the FASTQ format, Phred scores are represented as single ASCII letters. For details on translating between Phred scores and ASCII values, refer to Table 1 of this useful blog post from Damian Gregory Allis.

read-length: the number of base pairs that are sequenced in an individual sequence read.

read-depth: the number of sequence reads that pile up at the same genomic location. For example, 30X read-depth coverage indicates that the genomic location is covered by 30 independent sequencing reads. Increased read-depth translates into higher confidence for calling genomic variants.

RNAME: reference genome identifier (also known as the Reference Name). Within a SAM formatted file, the RNAME identifies the reference genome where the raw read aligns.

SAM Flag: a single integer value (e.g. 16), which encodes multiple elements of meta-data regarding a read and its alignment. Elements include: whether the read is one part of a paired-end read, whether the read aligns to the genome, and whether the read aligns to the forward or reverse strand of the genome. A useful online utility decodes a single SAM flag value into plain English.

SAM Format: Text file format for storing sequence alignments against a reference genome. See also BAM Format.

SAMtools: widely used, open source command line tool for manipulating SAM/BAM files. Includes options for converting, sorting, indexing and viewing SAM/BAM files. The SAMtools distribution also includes bcftools, a set of command line tools for identifying and filtering genomics variants. Created by Heng Li, currently of the Broad Institute.

single-read sequencing: sequencing process where only one end of a DNA or RNA fragment is sequenced. Contrast with paired-end sequencing.

VCF Format: Variant call format. Text file format for storing genomic variants, including single nucleotide polymorphisms, insertions, deletions and structural rearrangements. See also BCF format.

NextGenerationSequencing
A high-throughput sequencing method which parallelizes the sequencing process, producing thousands or millions of sequences at once.

DeepSequencing
Techniques of nucleotide sequence analysis that increase the range, complexity, sensitivity, and accuracy of results by greatly increasing the scale of operations and thus the number of nucleotides, and the number of copies of each nucleotide sequenced.

Paired-EndSequencing
Sequence both ends of the same fragment and keep track of the paired data.

Adapter
Short oligonucleotides which are attached to the DNA to be sequenced. An adapter can provide a priming site for both amplification and sequencing of the adjoining, unknown nucleic acid.

Library
A collection of DNA fragments with adapters ligated to each end.

BridgeAmplification
Generation of in situ copies of a specific DNA molecule on an oligo-decorated solid support.

EmulsionPCR
A method for bead-based amplification of a library. A single adapter-bound fragment is attached to the surface of a bead, and an oil emulsion containing necessary amplification reagents is formed around the bead/fragment component. Parallel amplification of millions of beads with millions of single strand fragments produces a sequencer-ready library.

Alignment
Mapping of sequence reads to a known reference sequence

Referencesequence/genome 
A fully assembled version of a genome that can be used for mapping short DNA sequence reads for comparisons of genomes from various individuals

CoverageDepth
The number of nucleotides from reads that are mapped to a given position of reference genome.

Specificity 
The percentage of sequences that map to the intended targets out of total bases per run.

Uniformity 
The variability in sequence coverage across target regions.

Homopolymer
Uninterrupted stretch of a single nucleotide type (e.g., TTT or GGGGGG)

InDel
InDel stands for Insertion or deletion. A form of structural variation in which a DNA segment is either deleted or inserted.

SNP 

SNP stands for Single Nucleotide Polymorphism. A single base difference found when comparing the same DNA sequence from two different individuals.