• Bioconductor – A plethora of tools for analysis and comprehension of high-throughput genomic data, including 1500+ software packages. [ paper-2004 | web ]
• Biopython – Freely available tools for biological computing in Python, with included cookbook, packaging and thorough documentation. Part of the Open Bioinformatics Foundation. Contains the very useful Entrez package for API access to the NCBI databases. [ paper-2009 | web ]
• Bioconda – A channel for the conda package manager specializing in bioinformatics software. Includes a repository with 3000+ ready-to-install (with conda install) bioinformatics packages. [ paper-2018 | web ]
• BioJulia – Bioinformatics and computational biology infastructure for the Julia programming language. [ web ]
• Rust-Bio – Rust implementations of algorithms and data structures useful for bioinformatics. [ paper-2016 ]
• SeqAn – The modern C++ library for sequence analysis.

The Department of Informatics is a vacant position as a researcher in computer science, related to Computational Biology Unit (CBU), for 3 years.

The position is part of CBU Service Group and will focus on bioinformatic analysis project and especially the analysis of high-throughput data, including NGS (sequencing), and proteomics data.

The successful candidate will be part of the Norwegian bioinformatics platform's national helpdesk within the project ELIXIR.NO

Applicants must hold a PhD in a relevant subject such as computer science, mathematics, molecular biology and also possess expertise and experience in bioinformatics statistics and analysis of data from high-throughput molecular experiment.

Basic programming or scripting skills are required. Experience in Python, R, Perl, Linux-based operating systems and moreover knowledge of databases and web programming will be a strength for applicants.

We expect enthusiasm and independence and moreover the ability to work in an interdisciplinary team environment.

Good knowledge of English is required.

Salaries start at level 57 (code 1109/LR 24.1) by appointment. Further promotion occurs after
service seniority in the position (at grade 57-65). Of particularly highly qualified applicants may be considered a higher salary.

Further information about the position is available from the chair of the CBU,
Professor Inge Jonassen, e-mail: Inge.Jonassen @ ii.uib.no

The successful applicant must comply with the guidelines that apply at any given time the position.

State employment shall as far as possible reflect the diversity of the population. It is therefore an objective to achieve a balanced age and sex composition and the recruitment of persons with immigrant backgrounds. Persons with immigrant background are requested to apply for the position.

Women are particularly encouraged to apply. If the experts find that several applicants have approximately equivalent qualifications, the rules on equal in the Personnel Regulations for Academic Positions will be applied.

University of Bergen applies the principles of public openness when recruiting staff to scientific positions.

Information about the applicant may be made public even though the applicant has requested not to be named in the list of applicants. If the request does not host admitted to the result, the applicant shall be notified of this.

Send application, CV, certificates, diplomas, undergraduate work and a list of publications (list of publications) online by clicking on https://www.jobbnorge.no/jobbsoknet/login.aspx?returnurl=/jobbsoknet/jobapplication.aspx?jobid=95196

You need to upload certified translations into English or a Scandinavian language of appendices, such as diplomas and transcripts.

Applications sent by email to individuals at the institute will not be considered.

Deadline: 9 August 2013

*The journals are not listed in any ascending, descending, or impact factors oders. 

Bioinformatics 

Journal of Computational Biology

Briefings in Bioinformatics

In Silico Biology

Structure

Protein Science

Protein Engineering

Proteomics

Nucleic Acids Research

Trends in Biotechnology

Proceedings of the National Academy of Sciences

Folding and Design

Genome Biology

Journal of Biomedical Informatics

Bioinformation

Journal of Computational Intelligence in Bioinformatics

Journal of Structural and Functional Genomics

Journal of Molecular Graphics and Modelling

Metabolic Engineering

Computers & Chemistry

Artificial Intelligence in Medicine

Journal of Biomedical Science

Artificial Intelligence

Machine Learning

Applied Bioinformatics

Applied Genomics and Proteomics

BMC Bioinformatics

Online Journal of Bioinformatics (OJB)

PSB On-Line Proceedings

Bioinformatics: Information Technology & Systems (BITS)

Data Mining and Knowledge Discovery

The EMBO Journal

Current Opinions in Structural Biology

Journal of Molecular Microbiology and Biotechnology

Nature

Nature Structural Biology

Journal of Machine Learning Research

Nature Genetics

Current Opinion in Genetics & Development

Nature Biotechnology

Trends in Biochemical Sciences

Proteins: Structure, Function, and Genetics

Nature Cell Biology

Trends in Genetics

ChemBioChem

Trends in Molecular Medicine

Journal of Molecular Modelling

Trends in Pharmacological Sciences

Drug Discovery Today

Others Free Online Full-text Journals

• the Damerau–Levenshtein distance allows insertion, deletion, substitution, and the transposition of two adjacent characters;
• the longest common subsequence (LCS) distance allows only insertion and deletion, not substitution;
• the Hamming distance allows only substitution, hence, it only applies to strings of the same length.
• the Jaro distance allows only transposition.

use Text::Levenshtein qw(distance);

 print distance("foo","four");
 # prints "2"

 my @words     = qw/ four foo bar /;
 my @distances = distance("foo",@words);

 print "@distances";
 # prints "2 0 3"

use Algorithm::LCSS qw( LCSS CSS CSS_Sorted );
    my $lcss_ary_ref = LCSS( \@SEQ1, \@SEQ2 );  # ref to array
    my $lcss_string  = LCSS( $STR1, $STR2 );    # string
    my $css_ary_ref = CSS( \@SEQ1, \@SEQ2 );    # ref to array of arrays
    my $css_str_ref = CSS( $STR1, $STR2 );      # ref to array of strings
    my $css_ary_ref = CSS_Sorted( \@SEQ1, \@SEQ2 );  # ref to array of arrays
    my $css_str_ref = CSS_Sorted( $STR1, $STR2 );    # ref to array of strings

There are many different modules on CPAN for calculating the edit distance between two strings. Here's just a selection.

Text::LevenshteinXS and Text::Levenshtein::XS are both versions of the Levenshtein algorithm that require a C compiler, but will be a lot faster than this module.

The Damerau-Levenshtein edit distance is like the Levenshtein distance, but in addition to insertion, deletion and substitution, it also considers the transposition of two adjacent characters to be a single edit. The module Text::Levenshtein::Damerau defaults to using a pure perl implementation, but if you've installed Text::Levenshtein::Damerau::XS then it will be a lot quicker.

Text::WagnerFischer is an implementation of the Wagner-Fischer edit distance, which is similar to the Levenshtein, but applies different weights to each edit type.

Text::Brew is an implementation of the Brew edit distance, which is another algorithm based on edit weights.

Text::Fuzzy provides a number of operations for partial or fuzzy matching of text based on edit distance. Text::Fuzzy::PP is a pure perl implementation of the same interface.

String::Similarity takes two strings and returns a value between 0 (meaning entirely different) and 1 (meaning identical). Apparently based on edit distance.

Text::Dice calculates Dice's coefficient for two strings. This formula was originally developed to measure the similarity of two different populations in ecological research.

Applications are invited for the post of Project Assistant to work in the following
project.

• Title of the project: "A novel approach for the identification of key regulatory molecules and their pathways for Rheumatoid Arthritis" funded by Department of Science and Technology, New Delhi, Government of India.

• Project Assistant

• Essential Qualification: The minimum essential qualification would be M.Sc/B.Tech. in Bioinformatics/ Computer Science /Biotechnology.

• Salary : Rs. 8,000/month for a period of 3 years

Application in plain paper with following details: Name, Address, Date of Birth and Educational Qualifications and details of research experience with publications if any, may be sent to:

Mr. Sachidanand Singh,
Principal Investigator,
Department of Bioinformatics, School of Biotechnology and Health Sciences
Karunya University,
Karunya Nagar, Coimbatore- 641114

Ph.no: 09489677764, 09047654981

E-mail: sachidanand@karunya.edu

http://www.karunya.edu/bioinformatics/people/faculty/

Deadline : 25th August 2013

Advertisement: www.karunya.edu/bioinformatics/Project%20Assistant%20in%20SERB.pdf

awk '/pattern1/ {Actions}
/pattern2/ {Actions}' file

The working of Awk is as follows
Awk reads the input files one line at a time.
For each line, it matches with given pattern in the given order, if matches performs the corresponding action.
If no pattern matches, no action will be performed.
In the above syntax, either search pattern or action are optional, But not both.
If the search pattern is not given, then Awk performs the given actions for each line of the input.
If the action is not given, print all that lines that matches with the given patterns which is the default action.
Empty braces with out any action does nothing. It wont perform default printing operation.
Each statement in Actions should be delimited by semicolon.
Say you have data.tsv with the following contents:

$ cat data/test.tsv
contig1 ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG
contig2 ACTTTATATATT
contig3 ACTTATATATATATA
contig4 ACTTATATATATATA
contig5 ACTTTATATATT
By default Awk prints every line from the file.

$ awk '{print;}' data/test.tsv
contig1 ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG
contig2 ACTTTATATATT
contig3 ACTTATATATATATA
contig4 ACTTATATATATATA
contig5 ACTTTATATATT
We print the line which matches the pattern contig3

$ awk '/contig3/' data/test.tsv
contig3 ACTTATATATATATA
Awk has number of builtin variables. For each record i.e line, it splits the record delimited by whitespace character by default and stores it in the $n variables. If the line has 5 words, it will be stored in $1, $2, $3, $4 and $5. $0 represents the whole line. NF is a builtin variable which represents the total number of fields in a record.

$ awk '{print $1","$2;}' data/test.tsv
contig1,ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG
contig2,ACTTTATATATT
contig3,ACTTATATATATATA
contig4,ACTTATATATATATA
contig5,ACTTTATATATT

$ awk '{print $1","$NF;}' data/test.tsv
contig1,ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG
contig2,ACTTTATATATT
contig3,ACTTATATATATATA
contig4,ACTTATATATATATA
contig5,ACTTTATATATT

Awk has two important patterns which are specified by the keyword called BEGIN and END. The syntax is as follows:

BEGIN { Actions before reading the file}
{Actions for everyline in the file}
END { Actions after reading the file }

For example,
$ awk 'BEGIN{print "Header,Sequence"}{print $1","$2;}END{print "-------"}' data/test.tsv
Header,Sequence
contig1,ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG
contig2,ACTTTATATATT
contig3,ACTTATATATATATA
contig4,ACTTATATATATATA
contig5,ACTTTATATATT
-------
We can also use the concept of a conditional operator in print statement of the form print CONDITION ? PRINT_IF_TRUE_TEXT : PRINT_IF_FALSE_TEXT. For example, in the code below, we identify sequences with lengths > 14:

$ awk '{print (length($2)>14) ? $0">14" : $0"<=14";}' data/test.tsv
contig1 ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG>14
contig2 ACTTTATATATT<=14
contig3 ACTTATATATATATA>14
contig4 ACTTATATATATATA>14
contig5 ACTTTATATATT<=14
We can also use 1 after the last block {} to print everything (1 is a shorthand notation for {print $0} which becomes {print} as without any argument print will print $0 by default), and within this block, we can change $0, for example to assign the first field to $0 for third line (NR==3), we can use:

$ awk 'NR==3{$0=$1}1' data/test.tsv
contig1 ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG
contig2 ACTTTATATATT
contig3
contig4 ACTTATATATATATA
contig5 ACTTTATATATT
You can have as many blocks as you want and they will be executed on each line in the order they appear, for example, if we want to print $1 three times (here we are using printf instead of print as the former doesn't put end-of-line character),

$ awk '{printf $1"\t"}{printf $1"\t"}{print $1}' data/test.tsv
contig1 contig1 contig1
contig2 contig2 contig2
contig3 contig3 contig3
contig4 contig4 contig4
contig5 contig5 contig5
Although, we can also skip executing later blocks for a given line by using next keyword:

$ awk '{printf $1"\t"}NR==3{print "";next}{print $1}' data/test.tsv
contig1 contig1
contig2 contig2
contig3
contig4 contig4
contig5 contig5

$ awk 'NR==3{print "";next}{printf $1"\t"}{print $1}' data/test.tsv
contig1 contig1
contig2 contig2

contig4 contig4
contig5 contig5
You can also use getline to load the contents of another file in addition to the one you are reading, for example, in the statement given below, the while loop will load each line from test.tsv into k until no more lines are to be read:

$ awk 'BEGIN{while((getline k <"data/test.tsv")>0) print "BEGIN:"k}{print}' data/test.tsv
BEGIN:contig1 ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG
BEGIN:contig2 ACTTTATATATT
BEGIN:contig3 ACTTATATATATATA
BEGIN:contig4 ACTTATATATATATA
BEGIN:contig5 ACTTTATATATT
contig1 ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG
contig2 ACTTTATATATT
contig3 ACTTATATATATATA
contig4 ACTTATATATATATA
contig5 ACTTTATATATT
You can also store data in the memory with the syntax VARIABLE_NAME[KEY]=VALUE which you can later use through for (INDEX in VARIABLE_NAME) command:

$ awk '{i[$1]=1}END{for (j in i) print j"<="i[j]}' data/test.tsv
contig1<=1
contig2<=1
contig3<=1
contig4<=1
contig5<=1

For more information visit: http://www.snubi.org/TBC2013/

https://edu.t-bio.info/collaborative-model-bioinformatics-education-combining-biologically-inspired-bioinformatics-project-based-learning/

http://biopython.org/DIST/docs/tutorial/Tutorial.html