Download JAR files tagged by herein with all dependencies

Retrofit ships with support for OkHttp's RequestBody and ResponseBody types but the library is content-format agnostic. This modules contained herein are additional converters for JSON which uses FastJson.

The refcodes-licensing artifact is a meta-artifact included as a dependency into all artifacts which apply the herein contained licensing terms (usually artifacts of the group org.refcodes). Them refcodes- licensing terms and conditions can be summarized as below. Please see the refcodes-licensing artifact of the version being applied to the artifact in question for the terms and conditions effectively being applied.

This project is a project for the JCoRe Linnaeus Annotator. The dictionary contained herein is used for the recognition of concrete species names in text, e.g. "human", "mouse", "n. furzeri", "c. elegans" etc. It does not contain species proxies, i.e. indirect clues to a species like the word "patient" which most likely refers to a human. For this task there is the project jcore-linnaeus-species-ae-proxies-dict.

This project is a resource for the JULES Linnaeus Annotator. The dictionary contained herein is 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. For the task of only finding concrete species names in text, there is the project jcore-linnaeus-species-ae-species-dict.

Metro is a high-performance, extensible, easy-to-use web service stack. It is a one-stop shop for all your web service needs, from the simplest hello world web service to reliable, secured, and transacted web service that involves .NET services. This module provides source files in order to produce Javadoc for Java EE. The set of files contained herein does not match what is in webservices-api.

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.