BIOJAVA TUTORIAL PDF

This chapter examines the Sequence interface. This adds extra functionality to SymbolList , providing a convenient way to handle annotated sequences from biological database. This chapter concentrates on classes and interfaces defined in the package org. Sequence is a sub-interface of SymbolList. Thus, all the standard methods for accessing sequence data in a symbol list can equally be applied to a sequence, and sequences can be passed to any analysis methods which normally expect to receive a symbol list. The Sequence interface adds two types of additional data to a symbol list:.

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BioJava is an open-source project that provides a Java library for processing biological data. The project aims to simplify bioinformatic analyses by implementing parsers, data structures, and algorithms for common tasks in genomics, structural biology, ontologies, phylogenetics, and more.

Since , we have released two major versions of the library 4 and 5 that include many new features to tackle challenges with increasingly complex macromolecular structure data. PLoS Comput Biol 15 2 : e This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: BioJava is not formally funded by any grants. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests: The authors have declared that no competing interests exist.

BioJava was launched in as an open-source Java library for bioinformatics focused on biological sequences and alignments [ 1 ]. The functionality of the library has grown over the years, ranging from parsers for common biological file formats to state-of-the-art tools for sequence and structural comparisons [ 2 ].

Following the major rewrite of the code base in version 3, the library consists of eleven independent modules that provide access to biological sequences, structures and common bioinformatics routines [ 3 ].

In addition to mature data structures for sequence analysis, recent work has yielded an expansion in features for analyzing macromolecular structure data. BioJava has also adopted best practices in software engineering, including continuous integration, unit testing, and code review.

Adherence to these practices makes BioJava suitable for inclusion in major bioinformatics pipelines, databases and software. BioJava is a popular option for method and software development thanks to the tooling available for Java and its cross-platform portability.

Other popular projects like BioPerl [ 4 ] and BioPython [ 5 ] offer great scripting flexibility, now also available in the Java world via the JVM-based scripting languages. At present, BioJava is a well-established project and continues to be actively maintained by a diverse user and developer community.

The library has accepted contributions from 65 different developers since , accumulated forks and stars on GitHub, and BioJava binaries were downloaded more than 19 thousand times over the last year.

The BioJava library is organized into several modules for maximum flexibility. Users can choose what subset of modules to depend on in their projects. The core module provides interfaces and routines to work with protein and nucleotide sequences.

Some of the functionality includes parsing sequences from local files and remote resources, conversion between file formats and gene to protein translation. This module acts as a base module and others can depend on it.

The alignment module supplies standard algorithms and data structures for pairwise and multiple sequence alignments. The structure module provides data structures and algorithms to parse, manipulate and compare 3D structures of biological macromolecules, and the structure-gui module allows visualization of structures and structure alignments in Jmol [ 8 ].

Other smaller modules provide more specific functionality for different Bioinformatics fields. For protein analyses, the aa-prop module provides a range of physicochemical properties e.

Survival analyses using the Kaplan-Meier estimator [ 11 ] are possible with the survival module. The ontology module adds support for ontologies and parsing OBO files. And finally, several bioinformatics services can be accessed using REST protocols using the ws module. A number of new features have been added to BioJava in the last few years, most of which are related to structural biology data handling.

Below we highlight a few of the most relevant. BioJava uses a hierarchical data model to represent biological structures. Instances of molecular entities chains are separated into 2 types: polymeric and non-polymeric chains, facilitating the traversal of the data and explicitly separating small molecules ligands, cofactors, ions, etc. BioJava implements a wide range of pairwise structure alignment algorithms to perform rigid, flexible, and non-topological alignments.

We introduced a custom implementation of the CE-MC procedure [ 14 ] in the org. Results are stored in a novel hierarchical data structure that supports rigid, flexible, and non-topological multiple structure alignments.

Tools to manage and visualize alignments have also been adapted to enable multiple aligned structures, as demonstrated in Fig 1. More information can be found in the BioJava tutorial. Implementations of CE-CP and CE-MC were used for the structural alignment, visualized using the Jmol based structure panel left , the multiple alignment panel top right , and a Forester based dendrogram of structural similarities bottom right. BioJava provides extensive functionality for working with macromolecular assemblies.

Protein complexes can be efficiently aligned using the QsAlign method [ 15 ] in the org. Global, local and internal within chains symmetry can also be detected using the QuatSymmetryDetector and CeSymm [ 16 ] methods in org.

Moreover, code for reconstruction of the crystal lattice via space group operators is available in the org. An efficient spatial hashing algorithm now permits rapid computation of networks of contacts within a macromolecule and between two distinct macromolecules. Contacts can be exposed on a per atom pair basis or summarized at the residue pair level.

An implementation of the rolling ball algorithm by Shrake and Rupley [ 17 ] was contributed to the structure module. This functionality enables surface accessibility calculations at any level of the structure hierarchy. Features such as calculation of relative surface area and buried surface area upon complex formation are now supported.

Secondary structure assignments from DSSP [ 19 ] can now be parsed from local and remote files or calculated from scratch using a custom implementation of the algorithm in org. This allows the representation of the 8 possible secondary structure types for any protein structure, even the largest ones in the PDB. The GenBank parser in org. BioJava releases depend on the number and importance of contributions made to the library. Since version 4, the semantic versioning philosophy has been strictly followed.

Changes that break the API represent new major releases, additions to the API are minor releases, and bug fixes are regarded as bugfix releases. We have since released two major versions of the library version 4 in January and version 5 in March , and two minor releases for BioJava 4 and one for BioJava 5.

In addition, we routinely released bugfix versions every few months. In December , the library is at version 5. Throughout its history, the BioJava library has been widely adopted in the scientific community, as demonstrated by the number of BioJava mentions and citations in scientific publications Fig 2. BioJava is a general purpose bioinformatics library, so it can be used in a broad range of research projects.

Examples in the literature include scripting for biological data analysis, the development of novel computational methods, and the creation of integration platforms and web servers for bioinformatics applications. In addition, the open philosophy of the project enhances collaboration between developers, so that many users of the library have eventually contributed back and become developers.

The extensive support of BioJava in basic operations like parsing and manipulating sequences and structures allows developers of novel algorithms to focus all their efforts on the bioinformatics problem itself.

For example, BioJava has recently been part of the development of altORFev [ 20 ], a method to predict alternative open reading frames in eukaryotic mRNAs, CE-Symm [ 16 ], a detector of internal symmetry in protein structures, and EPPIC [ 21 ], a predictor of biological assemblies in crystal structures. BioJava can also be used for large-scale bioinformatics applications. BioJava is also used by CloudPhylo [ 22 ], a tool written in Scala and built on Spark that is capable of processing large-scale genomic datasets for phylogeny reconstruction.

As another example, BioJava methods were used to compare thousands of protein assembly models to experimental structures during the assessment of biological assemblies in CASP12 [ 23 ]. In recent years the JVM platform has grown beyond the Java language itself.

A plethora of scripting languages that can interoperate with Java libraries have appeared, e. Scala, Kotlin, Clojure or Groovy. As a JVM-based library, BioJava can be seamlessly integrated into software written in any of those languages, and a few examples can already be found in the literature.

Last but not least, BioJava is a popular choice for the development of software platforms and web services that integrate several different bioinformatics applications. BioJava is also widely used by the RCSB Protein Data Bank PDB for their web-services [ 27 ], including protein quaternary symmetry annotation and visualization, structural comparisons and the exploration of protein modifications.

BioJava is an open-source project driven by the community. The library is currently hosted on GitHub, a platform that has simplified project management and enabled best practices in software engineering. BioJava 5 is a mature library with extensive support for a wide range of bioinformatics applications.

Work in recent years has been focused on tackling challenges with complex structural bioinformatics data. In the coming years, effort will continue to improve usability and stability, whilst reaching into new types of data from new experimental methods and growing bioinformatics fields like genomics and the integration into scientific workflows.

The Open Source philosophy will remain central to BioJava, as the project was founded on the firm belief that transparency promotes reproducible science, faster development through scientific and technical contributions by the community, and more robust and better documented code.

We thank all of the many BioJava users and developers who keep the library up and running. Abstract BioJava is an open-source project that provides a Java library for processing biological data.

Introduction BioJava was launched in as an open-source Java library for bioinformatics focused on biological sequences and alignments [ 1 ]. Design and implementation The BioJava modules The BioJava library is organized into several modules for maximum flexibility. New features A number of new features have been added to BioJava in the last few years, most of which are related to structural biology data handling.

Updated structure data model. New structure file formats. Multiple structural alignments. Download: PPT. Fig 1. Multiple structure alignment of circularly permuted lectins generated and visualized with BioJava.

Support for protein assemblies. Accessible surface area. Secondary structure. Improved genomic parsers. BioJava release cycle BioJava releases depend on the number and importance of contributions made to the library.

Results Throughout its history, the BioJava library has been widely adopted in the scientific community, as demonstrated by the number of BioJava mentions and citations in scientific publications Fig 2.

Fig 2. BioJava for method development The extensive support of BioJava in basic operations like parsing and manipulating sequences and structures allows developers of novel algorithms to focus all their efforts on the bioinformatics problem itself.

Integration into large-scale analyses BioJava can also be used for large-scale bioinformatics applications.

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GitHub is home to over 50 million developers working together to host and review code, manage projects, and build software together. If nothing happens, download GitHub Desktop and try again. Go back. If nothing happens, download Xcode and try again. If nothing happens, download the GitHub extension for Visual Studio and try again. The goal of this tutorial is to provide an educational introduction into some of the features that are provided by BioJava.

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BioJava is an open-source software project dedicated to provide Java tools to process biological data. BioJava supports a huge 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. Additional projects from BioJava include rcsb-sequenceviewer, biojava-http, biojava-spark, and rcsb-viewers.

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BioJava is an open-source project that provides a Java library for processing biological data. The project aims to simplify bioinformatic analyses by implementing parsers, data structures, and algorithms for common tasks in genomics, structural biology, ontologies, phylogenetics, and more. Since , we have released two major versions of the library 4 and 5 that include many new features to tackle challenges with increasingly complex macromolecular structure data. PLoS Comput Biol 15 2 : e This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: BioJava is not formally funded by any grants. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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