Free biological psychology software for linux

Bio::GMOD is a unified API for Model Organism Databases.

SYNOPSIS

Check the installed version of a MOD
use Bio::GMOD::Util::CheckVersions.pm
my $mod = Bio::GMOD::Util::CheckVersions->new(-mod=>WormBase);
my $version = $mod->live_version;
Update a MOD installation
use Bio::GMOD::Update;
my $mod = Bio::GMOD::Update->new(-mod=>WormBase);
$gmod->update();
Fetch a list of genes from a MOD
use Bio::GMOD::Query;
my $mod = Bio::GMOD::Query->new(-mod=>WormBase);
my @genes = $mod->fetch(-class=>Gene,-name=>unc-26);

Bio::GMOD is a unified API for accessing various Model Organism Databases. It is a part of the Generic Model Organism Database project, as well as distributed on CPAN.

MODs are highly curated resources of biological data. Although they typically incorporate sequence data housed at community repositories such as NCBI, they place this information within a framework of biological fuction gelaned from the published literature of experiments in model organisms.

Given the great proliferation of MODs, cross-site data mining strategies have been difficult to implement. Such strategies typically require a familiarity with both the underlying data model and the historical vocabulary of the model system.

Furthermore, the quickly-evolving nature of these projects have made installing a MOD locally and keeping it up-to-date a delicate and time-consuming experience.

Biomolecule Toolkit project is an Open Source library for the structural modeling of biological macromolecules. The toolkit provides a C++ interface for common tasks in computational structural biology, to facilitate the development of molecular modeling, design, and analysis tools.
Enhancements:
Documentation updates
- Addition of an extensive discussion of the leastsquares_superposition and RMSD-calculation methods, including a description of the mathematical theory behind their operation.
- Fully documented the rotation/translation methods
- Addition of a documented example program ("gyration_radius.cpp")
Bug fixes
- Fixed copy construction bug in PDBAtomDecorator that caused compilation errors in rare situations.
- Fixed a bug in PDBFileParser that caused a compilation error in the PDBSystem copy constructor.
- Fixed a const-conversion bug in GroupedElementIterator which prevented proper interoperation of const and non-const iterator types.
- Fixed a crash-producing bug in stream output for the TypeID class.
- Fixed a math error in RMSD and superposition methods that would corrupt molecule coordinates.
- Fixed a bug that caused all default-constructed PDBAtom objects to be treated as HETATMs.
Feature additions
- Added operator[] to AtomicStructure and PolymerStructure-derived classes.
- Added protected increment() and decrement() operators to TypeID class.
- PDBFileParser can now handle PDB files with ill-formed residue numbering (i.e. Files where residue numbers are repeated in successive chains).

Bio::Seq is a sequence object, with features.

SYNOPSIS

# This is the main sequence object in Bioperl

# gets a sequence from a file
$seqio = Bio::SeqIO->new( -format => embl , -file => myfile.dat);
$seqobj = $seqio->next_seq();

# SeqIO can both read and write sequences; see Bio::SeqIO
# for more information and examples

# get from database
$db = Bio::DB::GenBank->new();
$seqobj = $db->get_Seq_by_acc(X78121);

# make from strings in script
$seqobj = Bio::Seq->new( -display_id => my_id,
-seq => $sequence_as_string);

# gets sequence as a string from sequence object
$seqstr = $seqobj->seq(); # actual sequence as a string
$seqstr = $seqobj->subseq(10,50); # slice in biological coordinates

# retrieves information from the sequence
# features must implement Bio::SeqFeatureI interface

@features = $seqobj->get_SeqFeatures(); # just top level
foreach my $feat ( @features ) {
print "Feature ",$feat->primary_tag," starts ",$feat->start," ends ",
$feat->end," strand ",$feat->strand,"n";

# features retain link to underlying sequence object
print "Feature sequence is ",$feat->seq->seq(),"n"
}

# sequences may have a species

if( defined $seq->species ) {
print "Sequence is from ",$species->binomial_name," [",$species->common_name,"]n";
}

# annotation objects are Bio::AnnotationCollectionIs
$ann = $seqobj->annotation(); # annotation object

# references is one type of annotations to get. Also get
# comment and dblink. Look at Bio::AnnotationCollection for
# more information

foreach my $ref ( $ann->get_Annotations(reference) ) {
print "Reference ",$ref->title,"n";
}

# you can get truncations, translations and reverse complements, these
# all give back Bio::Seq objects themselves, though currently with no
# features transfered

my $trunc = $seqobj->trunc(100,200);
my $rev = $seqobj->revcom();

# there are many options to translate - check out the docs
my $trans = $seqobj->translate();

# these functions can be chained together

my $trans_trunc_rev = $seqobj->trunc(100,200)->revcom->translate();

A Seq object is a sequence with sequence features placed on it. The Seq object contains a PrimarySeq object for the actual sequence and also implements its interface.

In Bioperl we have 3 main players that people are going to use frequently

Bio::PrimarySeq - just the sequence and its names, nothing else.
Bio::SeqFeatureI - a location on a sequence, potentially with a sequence
and annotation.
Bio::Seq - A sequence and a collection of sequence features
(an aggregate) with its own annotation.

Although Bioperl is not tied heavily to file formats these distinctions do map to file formats sensibly and for some bioinformaticians this might help

Bio::PrimarySeq - Fasta file of a sequence
Bio::SeqFeatureI - A single entry in an EMBL/GenBank/DDBJ feature table
Bio::Seq - A single EMBL/GenBank/DDBJ entry

By having this split we avoid a lot of nasty circular references (sequence features can hold a reference to a sequence without the sequence holding a reference to the sequence feature). See Bio::PrimarySeq and Bio::SeqFeatureI for more information.

Ian Korf really helped in the design of the Seq and SeqFeature system.

libMAGE is a Multi-Agent Grid Engine library. libMAGE library an experiment aimed to make a programming tool for creation of autonomic systems. We define autonomic system as the system that has the following features:

- The system is composed from a set of intellectual agents. All decision-making in the system is distributed and has a form of self-organization.
- The system is able to adapt to the surrounding environment. This includes adaptation to CPU, memory and disk load, and node failure (self-healing). The system is allowed to allocate additional nodes or redistribute current resources.

In libMAGE every agent of the system can be viewed as a living cell in a biological organism. Every agent contains enough information for construction of the whole organism, however after going through the process of growth, which mimics morphogenesis, the agent gets specialized. Specialized agents form groups and function cooperatively.

Bio::ConnectDots::ConnectDots is a top level class for connect-the-dots.

SYNOPSIS

use Bio::ConnectDots::DB;
use Bio::ConnectDots::ConnectDots;

my $db=new Bio::ConnectDots::DB(-database=>test,
-host=>computername,
-user=>usename,
-password=>secret);
my $cd=my $cd=new Bio::ConnectDots::ConnectDots(-db=>$db);

This is the top level class for Connect the Dots. At present, it mainly provides methods for running queries.
Connect the Dots is a general data integration framework targeted at translating biological identifiers across multiple transitive databases. This software provides an alternative to writing custom parsers to join databases on common identifiers. See the example queries for details on the scope of database joins that can be made.

This software is built upon the PostgreSQL database system (developed with version 7.4.3) as support for full outer joins is strong.

GENESIS (short for GEneral NEural SImulation System) is a general purpose simulation platform that was developed to support the simulation of neural systems ranging from subcellular components and biochemical reactions to complex models of single neurons, simulations of large networks, and systems-level models.

GENESIS has provided the basis for laboratory courses in neural simulation at Caltech, the Marine Biological Laboratory, the Crete, Trieste, Bangalore, and Obidos short courses in Computational Neuroscience, and at least 49 universities of which we are aware.

Most current GENESIS applications involve realistic simulations of biological neural systems. Although the software can also model more abstract networks, other simulators are more suitable for backpropagation and similar connectionist modeling.

Installation

1. Pick the place where you want to install the "genesis" directory tree. If you are making a system-wide installation as "root" user, /usr/local is a good choice. For a personal installation, without root privileges, you can use your home directory ("~"). Change to this directory and extract the genesis directory from the archive file genesis2.2.1-linux-bin.tar.gz. For example,

cd /usr/local
tar xvzf /mnt/cdrom/genesis2.2.1-linux-bin.tar.gz

or from wherever you have it (e.g.~/downloads/genesis2.2.1-linux-bin.tar.gz).

2. Change to the "genesis" directory and run the setup script that creates the ".simrc" GENESIS initialization file". Then copy .simrc to your home directory.

cd genesis
./binsetup
cp .simrc ~

3. Finallly, add the genesis directory to your search path, so that "genesis" can be found from any directory that you are in. If your login shell is bash, you can do this by editing the .bashrc file in your home directory to add the line

PATH=$PATH:/usr/local/genesis

at the end of the file. If you are using tcsh or csh as your command shell, add

set path=($path /usr/local/genesis)

to your .tcsh or .csh file.

At this point, you are ready to try running GENESIS. Change into the directory genesis/Scripts and try some of the tutorials suggested in the README file.

Citation project is a web based tool for bibliographic conversions.
Citation is a bibliographical conversion program designed to transform data between several different formats including GTEC, Refer, and Bibtex.
This program saves the researcher time by keeping unnecessary formatting from taking up their time. Currently, Citation is written in Java.
The use of Java moves much of the processing of the program to the users machine.
After downloading the Citation applet, the user is free to log off the network, but can still continue using the Citation applet.
Main features:
- Citation is available in both applet format and command line driven application.
- The Citation applet has the ability to convert between single or multiple entries.
- The Citation application is specifically designed for batch processing of files.
- Easy to use interface.
- Citation 1.7 supports format conversion from: INSPEC, ENGI, GTEC, PSYCH, Refer, and Bibtex to: Refer, Bibtex, HFS (Handbook for Scholars), Chicago Manual of Style, MLA (Modern Language Association), APA (American Psychology Association), and Galileo formats: ABI and Periodicals.
- Citation 1.7 has added new input manual format where user can add his or her own inputs in the input boxes rather than cut and pasting. This also supports format conversion mentioned previously.