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Annotation based model factory for Java. A Model is mapped by a Blueprint using annotated fields. Blueprints contain default values and references to other blueprinted models. The ModelFactory can create Models based on registered Blueprints. A Model already created can be passed into the ModelFactory as a Reference Model, which will be used as the basis for the new Model.

Model Citizen is an annotation based model factory for Java. A Model is mapped by a Blueprint using annotated fields. Blueprints contain default values and references to other blueprinted models. The ModelFactory can create Models based on registered Blueprints. A Model already created can be passed into the ModelFactory as a Reference Model, which will be used as the basis for the new Model.

Model Citizen is an annotation based model factory for Java. A Model is mapped by a Blueprint using annotated fields. Blueprints contain default values and references to other blueprinted models. The ModelFactory can create Models based on registered Blueprints. A Model already created can be passed into the ModelFactory as a Reference Model, which will be used as the basis for the new Model.

Model Citizen is an annotation based model factory for Java. A Model is mapped by a Blueprint using annotated fields. Blueprints contain default values and references to other blueprinted models. The ModelFactory can create Models based on registered Blueprints. A Model already created can be passed into the ModelFactory as a Reference Model, which will be used as the basis for the new Model.

Model Citizen is an annotation based model factory for Java. A Model is mapped by a Blueprint using annotated fields. Blueprints contain default values and references to other blueprinted models. The ModelFactory can create Models based on registered Blueprints. A Model already created can be passed into the ModelFactory as a Reference Model, which will be used as the basis for the new Model.

This project is a resource for the JCoRe Linnaeus Annotator. The dictionaries contained herein are used for the recognition of concrete species names in text, e.g. "human", "mouse", "n. furzeri", "c. elegans" etc as well as species hints, i.e. indirect clues to a species like the word "patient" which most likely refers to a human. Additionally to such rather clear proxies, this project also includes a small dictionary containing maximum-frequency-proxies for genus expressions like "Drosophila" which will be mapped to "D. melanogaster". For the task of only finding concrete species names in text, there is the project jcore-linnaeus-species-ae-species-dict.

This project has a lot of business classes to work with genes and related named entities. Genes are part of a GeneDocument and may have gold IDs as well as mapped/predicted IDs. Another large part are species because most (all?) gene ID databases are species specific. So there are also classes or members to represent species mentions and the assignment of species IDs (taxonomy IDs) to genes. There is little to no business logic herein. This project is only useful as building block in other projects dealing with species assignment, gene ID mapping or similar efforts.

In some data processing tasks we need to use huge maps or sets that are bigger than available JVM heap space or they are loading too slow to standard Java or Scala Maps. We use TSV format (text file with tab separated columns) for persist this kind of Maps or Sets. Some columns are used as a key and rest of columns as a value. Idea of this library is simple. We can prepare these maps once (sort by key), store it to file and then use it as memory mapped file. Searching key in sorted file has log(n) complexity. If more processes uses the same memory mapped file, it exists in memory just once (on Linux). This file can be loaded lazy by OS.

In some data processing tasks we need to use huge maps or sets that are bigger than available JVM heap space or they are loading too slow to standard Java or Scala Maps. We use TSV format (text file with tab separated columns) for persist this kind of Maps or Sets. Some columns are used as a key and rest of columns as a value. Idea of this library is simple. We can prepare these maps once (sort by key), store it to file and then use it as memory mapped file. Searching key in sorted file has log(n) complexity. If more processes uses the same memory mapped file, it exists in memory just once (on Linux). This file can be loaded lazy by OS.

In some data processing tasks we need to use huge maps or sets that are bigger than available JVM heap space or they are loading too slow to standard Java or Scala Maps. We use TSV format (text file with tab separated columns) for persist this kind of Maps or Sets. Some columns are used as a key and rest of columns as a value. Idea of this library is simple. We can prepare these maps once (sort by key), store it to file and then use it as memory mapped file. Searching key in sorted file has log(n) complexity. If more processes uses the same memory mapped file, it exists in memory just once (on Linux). This file can be loaded lazy by OS.