The content on this page was used during the development of the BioJava
- BioJava 3 has been released on December 28th 2010. The latest release
is available from
For information on the current status of the BioJava 3 implementation go to BioJava3_project
This document was based on comments made on the following pages:
- BioJava3 (BJ3) will freely incorporate features from Java 6.
- Maven will be used to build the project.
- Full unit testing for every aspect from the ground up using JUnit.
- Modular design without any cyclic dependencies, with separate JARs for key components (IO, databases, genetic algorithms, sequence manipulation, etc.)
- Separation of APIs from implementation code by means of packages.
- Base package name: org.biojava3 (to prevent clashes with org.biojava and org.biojavax, both of which will have backwards-compatibility extensions to BJ3 in order to make old code reusable).
- Use of JavaBeans concepts wherever possible, e.g. getters/setters. This would enhance Java EE compliance and improve integration into larger things. DON’T do this where immutability is key to efficiency though, like with Strings.
- Fully commented code in LOTS of detail INCLUDING package-level docs AND wiki-docs such as the cookbook.
- Use of annotations for things like database mappings.
- A consistent coding style to be developed and applied.
- No Swing code to be included, but graphics code is OK for obviously useful things such as protein structures or sequence traces. Swing code is impossible to write in a way that will integrate fully with each different individual’s own program requirements.
- Keep It Simple Stupid (KISS) - don’t object-ify things unless absolutely necessary. Sequences are perfectly happy as Strings unless you want to do complex things like store base quality information, and only at that point should you want to convert them into more complex object models.
- Separation of functionality - don’t make sequences load features, and don’t make features load their sequence by default. This saves memory and allows work to be done independently on the specific parts of interest.
- Always ALWAYS correctly implement equals, compareTo, hashCode, and Serializable wherever possible.
- Any general-use methods to be exposed via SPI (e.g. getTopBlastHit()).
- The source code license will be the GNU Lesser General Public License (LGPL) “version 2.1 or any later version”.
- In general BJ3 exceptions should be RuntimeExceptions and unchecked. They should also be well documented and give useful messages. It should be up to the developer to decide what to capture and what not to. In the current BioJava there are way to many exceptions that can’t really happen under any normal circumstances. We should only need to think about exceptions in exceptional circumstances.
- The default Java logging API should be used extensively. This will allow a developer the ability to fine tune debugging. The core module should have a logging helper with static convenience methods to make it very easy to liberally use logging calls via static imports.
Compromises and Unfinished bits
- TestNG was suggested instead of JUnit, but knowledge of this tool is not so widespread and this may impact on quality of testing.
- A tool for analysing comment coverage and coding style was suggested, but none have been identified. Please amend this document with the names of any good ones you know.
[Jalopy http://jalopy.sourceforge.net/] - can be used as Eclipse
plugin, or Ant task.
[Cobertura http://cobertura.sf.net] - can be used to assess JUnit test coverage.
[FindBugs http://findbugs.sf.net] - does static analysis of code (also runnable as Eclipse plugin or Ant task.
Andreas’ very useful Usage Analysis page shows the most frequently requested documentation. In the absence of any real usage statistics, we must assume that the things people most often want to read about are the things that people most often use. (It could also be said that the things that people most read about are the things that work least well in the present code… but we shall ignore that for now…).
Here are the priorities based on Andreas’ work:
- How to get an Alphabet
- How to make a Sequence Object from a String or make a Sequence Object back into a String
- How to parse a Blast output
- How to read sequences from a Fasta file
- How to read a GenBank, SwissProt or EMBL file
- How to generate a global or local alignment with the Needleman-Wunsch- or the Smith-Waterman-algorithm
- How to read a protein structure - PDB file
- How to export a sequence to fasta
- How to view a sequence in a gui
- How to parse a Fasta database search output file
These can be broken down into the following modules:
- Plain sequence <-> Enriched sequence
- Sequence similarity -> Sequence similarity IO (Blast, Fasta, etc.)
- Plain sequence -> Plain sequence IO (Genbank, FASTA, etc.)
- Enriched sequence -> Sequence alignments
- Enriched sequence -> Protein structures
- BioJava3 module
- API module contains object builder signature (builder builds objects from events, much like a SAX parser does).
- Listeners can choose to cache data in memory, on disk, keep a pointer to the source and read it back later, or whatever. Up to them. Optimisation becomes easier this way as listeners can choose exactly what to keep in memory and what not to.
- Sequence module
- API module defines entire BioJava sequence object model (similar to current one but allowing for non-symbol based sequences and separation of sequences from features).
- API has subclasses of object builders for sequences. Builder can specify it is only interested in certain events, and parsers can query this to optimise parsing by skipping irrelevant sections.
- Conversion to symbol-based sequences on demand to/from strings.
- Simplified alphabet concept, made easier by avoiding use of XMLs to configure them.
- WATCH OUT for localised strings when manipulating sequences.
- WATCH OUT for singletons and multi-processor environments. Consider using JNDI if they are absolutely necessary.
- Feature module
- API module defines entire BioJava feature object model (similar to current one but allowing for separation of sequences from features).
- API has subclasses of object builders for features. Builder can specify it is only interested in certain events, and parsers can query this to optimise parsing by skipping irrelevant sections.
- Allow feature naming using any of the standard ontologies.
- IO module
- API module contains basic read() and write() function signatures.
- API has concept of RecordSource which is either a file, a group of files (e.g. directory), a database, a web service, etc. - all of which implement some kind of RecordProvider interface for iterating over objects. Those objects can be sequences, features, etc.
- Implementation module - one per sequence format - e.g. Genbank, FASTA, etc.
- Use of event listeners to fire events at an object builder.
- Each implementation has default object model and builder that exactly matches that format, along with a converter that will ‘read’ the object model and fire events as if it was being read again (to allow for conversion to other formats via the listener framework).
- BioSQL is an IO module. So are other dbs, e.g. Entrez, ebEye.
- A RecordSearch API to be implemented to search for matching records in any RecordSource.
- LazyLoading where possible.
- Input AND Output achieved by SAX-like event firing. Reading a file fires events at an object builder containing bits of data as they are read. Writing a file causes an object parser to parse an object and fire events at a file writer. Any listener can listen to any other source of events, so you can short-circuit file conversion by reading GenBank and specifying the reader-listener as an instance of a FASTA writer-listener.
- RecordSources to be versioned to cope with changing formats over time.
- Each IO module to be entirely independent and agnostic of the way it is used. This allows modules to optimise themselves for random access etc., if they see fit. By using the methods on the API to check what the listener is interested in receiving, they can also cut out the work of parsing uninteresting stuff.
- Other modules
- Ontology handling.
- Protein structure
- Microarray analysis
- etc. etc. etc.
It is planned to document BioJava in parallel with development. To do this, we want to drive development from a set of use cases.