BioJava: Инструменты для обработки биологических данных на Java

BioJava is an open source software project dedicated to provide Java tools to process biological data. BioJava is a set of library functions written in the programming language Java for manipulating sequences, protein structures, file parsers, Common Object Request Broker Architecture (CORBA) interoperability, Distributed Annotation System (DAS), access to AceDB, dynamic programming, and simple statistical routines. BioJava supports a range of data, starting from DNA and protein sequences to the level of 3D protein structures. The BioJava libraries are useful for automating many daily and mundane bioinformatics tasks such as to parsing a Protein Data Bank (PDB) file, interacting with Jmol and many more. Examples of such projects that fall under Bio* apart from BioJava are BioPython, BioPerl, BioRuby, EMBOSS etc. In October 2012, the first paper on BioJava was published. This paper detailed BioJava's modules, functionalities, and purpose. As of November 2018 Google Scholar counts more than 130 citations. The most recent paper on BioJava was written in February 2017. This paper detailed a new tool named BioJava ModFinder. This tool can be used for identification and subsequent mapping of protein modifications to 3D in the Protein Data Bank (PBD). The package was also integrated with the RCSB PDB web application and added protein modification annotations to the sequence diagram and structure display. More than 30,000 structures with protein modifications were identified by using BioJava ModFinder and can be found on the RCSB PDB website. In the year 2008, BioJava's first Application note was published. The project has been moved to a separate repository, BioJava legacy, and is still maintained for minor changes and bug fixes. Version 3 was released in December 2010. It was a major update to the prior versions. The aim of this release was to rewrite BioJava so that it could be modularized into small, reusable components. This allowed developers to contribute more easily and reduced dependencies. The new approach seen in BioJava 3 was modeled after the Apache Commons. Version 4 was released in January 2015. This version brought many new features and improvements to the packages biojava core, biojava structure, biojava structure gui, biojava phylo, as well as others. BioJava 4.2.0 was the first release to be available using Maven from the Maven Central. Version 5 was released in March 2018. This represents a major milestone for the project. BioJava 5.0.0 is the first released based on Java 8 which introduces the use of lambda functions and streaming API calls. There were also major changes to biojava structure module. Also, the previous data models for macro molecular structures have been adapted to more closely represent the mmCIF data model. This was the first release in over two years. Some of the other improvements include optimizations in the biojava structure module to improve symmetry detection and added support for MMTF formats. Other general improvements include Javadoc updates, dependency versions, and all tests are now Junit4. The release contains 1,170 commits from 19 contributors.

This module provides Java classes to model amino acid or nucleotide sequences. The classes were designed so that the names are familiar and make sense to biologists and also provide a concrete representation of the steps in going from a gene sequence to a protein sequence for computer scientists and programmers. A major change between the legacy BioJava project and BioJava3 lies in the way framework has been designed to exploit then new innovations in Java. A sequence is defined as a generic interface allowing the rest of the modules to create any utility that operates on all sequences. Specific classes for common sequences such as DNA and proteins have been defined in order to improve usability for biologists. The translation engine really leverages this work by allowing conversions between DNA, RNA and amino acid sequences. This engine can handle details such as choosing the codon table, converting start codons to methionine, trimming stop codons, specifying the reading frame and handing ambiguous sequences. Special attention has been paid to designing the storage of sequences to minimize space needs. Special design patterns such as the Proxy pattern allowed the developers to create the framework such that sequences can be stored in memory, fetched on demand from a web service such as UniProt, or read from a FASTA file as needed. The latter two approaches save memory by not loading sequence data until it is referenced in the application. This concept can be extended to handle very large genomic datasets, such as NCBI GenBank or a proprietary database.

This module contains several classes and methods that allow users to perform pairwise and multiple sequence alignment. Sequences can be aligned in both a single and multi threaded fashion. BioJava implements the Needleman Wunsch algorithm for optimal global alignments and the Smith and Waterman's algorithm for local alignments. The outputs of both local and global alignments are available in standard formats. In addition to these two algorithms, there is an implementation of Guan–Uberbacher algorithm which performs global sequence alignment very efficiently since it only uses linear memory. For Multiple Sequence Alignment, any of the methods discussed above can be used to progressively perform a multiple sequence alignment.

framed|right|An example application using the ModFinder module and the protein structure module. Protein modifications are mapped onto the sequence and structure of ferredoxin I (PDB ID 1GAO). Two possible iron–sulfur clusters are shown on the protein sequence (3Fe–4S (F3S): orange triangles/lines; 4Fe–4S (SF4): purple diamonds/ lines). The 4Fe–4S cluster is displayed in the Jmol structure window above the sequence display
The ModFinder module provides new methods to identify and classify protein modifications in protein 3D structures. Over 400 different types of protein modifications such as phosphorylation, glycosylation, disulfide bonds metal chelation etc. were collected and curated based on annotations in PSI MOD, RESID and RCSB PDB. The module also provides an API for detecting pre , co , and post translational protein modifications within protein structures. This module can also identify phosphorylation and print all pre loaded modifications from a structure.

As per the current trends in bioinformatics, web based tools are gaining popularity. The web service module allows bioinformatics services to be accessed using REST protocols. Currently, two services are implemented: NCBI Blast through the Blast URLAPI (previously known as QBlast) and the HMMER web service.