The BLAST algorithm and tool is possibly one of the most popular and important bioinformatics tools. BLAST is an algorithm that allows researchers to search a database of sequences (DNA or Amino Acid) for matches or similarities to their query sequence. BLAST is a heuristic algorithm so it isn’t as optimal as the Smith-Waterman algorithm but it is much faster and therefore generally more useful. For a detailed look into the BLAST algorithm check out the BLAST Wikipedia entry.

The first step is to download and install the BLAST+ tools onto your machine. Once you have done that you’ll find there are a number of different tools in the package. The main one that you will use to perform different blasts is blastall. Here is an example of it’s usage:

$ blastall -p blastn -d nr -e 10 -i inputfile -o outputfile

Common options are:
-p: blast program to use (blastn, blastp, blastx, …) See table below.
-d: database to use (defaults to nr) See section below.
-e: expectation value threshold (defaults to 10)
-i: input query sequence (In FASTA or Genbank format)
-o: output file name
All other options will be displayed if you run “blastall” without any arguments.

BLAST Programs

When running blastall you need to specify which blast you would like to perform (using the -p option). Below is a table of the different blast programs that blastall can run.

Database Usage

When you specify a database to query (using the -d option) you need to have a local copy of whichever database you want to use. If you want to use one of NCBI’s databases then you first need to download a copy of the database using the update_blastdb.pl script. Alternatively, if you have your own sequences that you want to use as your database then you need to use the makeblastdb tool (formerly formatdb) in order to format the sequences in a way that blastall can read. Here is an example of how to do this:

$ makeblastdb -i myseqs.fa -p T -n my_db

Common options are:
-i: input sequence file
-n: name of database to be created
-p: T or F if sequences to be parsed are in FASTA format

Once you have created your local database you can then try performing a BLAST on it:

$ blastall -p blastn -d my_db -i query_seq.fa -o outputfile

Hopefully this tutorial will help get you started using command line BLAST. If you have any further questions about some of the functionality not mentioned in this tutorial then leave a comment below and I will answer any of your questions.

BioPerl is a great set of open source modules for Perl programming. These modules simplify many of the common tasks that bioinformatics programmers regularly deal with. BioPerl saves the programmer lots of time so it is worth putting in a little bit of effort to become familiar with the modules.

BioPerl provides modules for many common bioinformatics tasks. Here are some of the features that BioPerl has modules for:

• Accessing sequence data from local and remote databases
• Transforming formats of database/ file records
• Manipulating individual sequences
• Searching for similar sequences
• Creating and manipulating sequence alignments
• Searching for genes and other structures on genomic DNA
• Developing machine readable sequence annotations

Head on over to BioPerl’s Website and learn more about BioPerl.

The basic answer is that Bioinformatics is the field where Computer Science, Biology, and Statistics meet. But even for a basic answer that is still too vague. I like to think of it as using Computer Science and Statistics to find and solve biological problems. Personally I like to think of Bioinformatics having two main focuses: Data Management and Research.

Data Management

A good chunk of Bioinformatics is devoted to purely Data Management, which is not an easy task considering the amount of data that Scientists generate. In the age of high-throughput machines, gigabytes of biological data can be produced in a matter of minutes or even seconds — particularly from machines that sequence DNA and Protein sequences and measure gene expression levels in a cell. The challenge lies in storing this data in databases in a way that will preserve the data and allow it to be easily accessible so it can be used in current and future research. The use of a number of different file formats adds even more complexity to this challenge.

Keeping the data accessible involves programming front-end applications to these databases that allow these large amounts of data to be viewed and interpreted. Extra care is taken to use optimal search algorithms so that the stored data can be quickly searched over. Computationally expensive algorithms are used to try and align sequences in order to find similar or exact matches. Using statistics, data mining techniques sometimes have to be used in order to extract the desired information from these vast databases.

Research

The Bioinformatics field is a research field so even within data management there is research being performed. Faster and more accurate computational algorithms are always sought after. New methods for biological data analysis are frequently being developed. Bioinformaticians use genomic and gene expression data to find new protein-protein interactions within cells. Algorithms and statistical methods are used to predict the location of genes within long strands of DNA sequences. The complex structures of DNA and Protein molecules are predicted.

The list of research being performed goes on and on. The current research and future potential of Bioinformatics is what makes this field exciting.