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Moara is an easy to use, handy biological text mining tool that consists of a Java library and some auxiliary MySQL databases for gene / protein training and extraction of mentions and its further normalization and disambiguation. Moara Features: ? Java Development: Library has been developed with Java programming language and a DOM parser to parse the XML format of Gene. Moara supports some of the most widely used ontologies for biological entities such as GO, Phenotype, Disease, Sequence Ontology, Protein Ontology, Drug Ontology and the mappings. Moara also supports the mappings between various databases and ontologies. ? Gene Extraction: Moara is equipped with an ontology-based method for the automatic extraction of known sequences as well as for the detection of existing (and new) proteins. ? Gene Mapping: Moara provides methods to map the mentions between Gene and Protein Entities (GO, Disease, Sequence Ontology, etc.), so that biologists can get data for example of all proteins produced from a given gene. For example if you have a gene which name is Beta-Sialolactone Synthase, there may be around 1000 genes, proteins, and products of genes in the Protein Ontology. Beta-Sialolactone Synthase produces one protein which has GO cellular component term – epidermis. Moara helps to detect if and which sequence of a gene is mapped to an ontology or map various ontologies (e.g. from INSDC, NCBI, SwissProt and UniProt). ? Sequence Based Protocols: Moara is easy to use, but it still provides a lot of options for the convenience of biologist. Moara provides operations such as substitution, cut-and-paste, addition, deletion, and rotation. ? Visualization: Moara provides an IDE to visualize ontology hierarchy and provide deep class level information. For example, if you have a gene which name is Beta-Sialolactone Synthase, there may be around 1000 genes, proteins, and products of genes in the Protein Ontology. Beta-Sialolactone Synthase produces one protein which has GO cellular component term – epidermis. Moara helps to detect if and which sequence of a gene is mapped to an ontology or map various ontologies (e.g. from INSDC, NCBI, SwissProt and UniProt). ? Gene Search: Moara can directly provide the

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Moara is an easy to use, BioText is an open-source molecular biology software package. It supports text search, highlighting, structural analysis, homology modeling, sequence retrieval, and integration with several biological databases. It is written in Java and has a GTK+/Cairo gui. Molecular Text is an open source free tool to extract and format small parts of proteins. There is a solution to extract text from any document, you can also use the tool to generate text that is suitable for display on the web page. The iText 2 Editor is a free, web-based text editor, to view and manage documents in Open Document Format(ODT), Office Open XML, XHTML and HTML files. In addition, the program is also a publishing tool: it can publish documents to the internet, print, create a PostScript file or create HTML, DOC, PDF, EXCEL, FLASH, MPEG4 and a wide range of graphics formats. The iText 2 editor has many features: import and export to other supported file types, creation of editing groups, text formatting, exporting of sources as images, conversion to other file types (HTML, PDF, DOC, XML, etc.), panning and scrolling, annotation, permissions management, and an… The Italian Text Mining infrastructure is a collection of text mining tools and services for biological and biomedical text mining that focus on the Italian language. The tools are available as open-source software packages under the GNU General Public License. TextFile is a simple open-source text processing and reporting engine. It can open, parse and search a text file, and then format the data in plain text. It is distributed under the General Public License (GPL) and is available for download free of charge. EuroTox21-Text is a text mining tool to create a list of toxicological endpoints from the Eurotox21 ToxRefDB database. It uses common text mining approaches to extract toxicological terms and the degree of severity (LD50, LD100, etc) from the ToxRefDB database. In addition, it reports the retrieved toxicological terms along with their associated degree of severity. TXTReader is a light and very simple text reader, built in Java. It can read and display the contents of TXT, RTF, and HTML files. It allows you to view and edit the contents of files from within your application. Stringological is a 91bb86ccfa

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Moara is an easy to use, handy biological text mining tool that consists of a Java library and some auxiliary MySQL databases for gene / protein training and extraction of mentions and its further normalization and disambiguation. The core component of Moara is a java library which is an implementation of the GENIA implementation. The GENIA implementation is a state of the art implementation of a rule based pipeline which is used by the LLLab to perform a complex biomedical text mining operation called gene normalization and gene mention disambiguation. This input to the GENIA pipeline is a XML-based text format file called SGNML that we call the SGNML file. The SGNML file can be created by a lab or by simply making a small modification to the CDM database. The MOARA library also includes the GENIA filtering component. This component uses the SGNML file to perform a supervised learning experiment against the GENIA annotated text corpus. Moara Platforms: The Moara JAR file is a platform independent library designed to run on all platforms including Windows, Linux, and Unix. This supports many of the same versions of Java that appear in common web browsers. Moara database component: Moara also includes an auxiliary database system for storing and retrieving the training and extraction results. Disambiguation Moara supports disambiguation for individual mentions in the SGNML file. The mechanism for resolving ambiguous mentions has been improved to allow for both contextual information and sequence-based disambiguation. Moara Features: SGNML format provides high accuracy disambiguation of single gene/protein / mention names using their unique sequence. The training data is captured from multiple expert created annotations for specific biomedical areas. Training data is stored in a relational database for retrieval and performing post processing on the raw data. Every time a new document comes in and is processed it is added to the same database tables so that the newly processed document can use the data that has already been processed for disambiguation. Moara Tutorial: The example below shows an XML document with mentions. Note the ‘@’ symbol preceding each mention and the notes that appear below each mention.

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[Wipro – NLP(Natural Language Processing)] Moara is designed to be used on any genome/protein data (in the form of FASTA/AB) or any set of data where the protein is identified by the UniProtKB ID. It is useful in the form of API that can be used with any other Java program. Its main functionalities include Gene/protein Extraction, mentions extraction and normalization of mentions to UniProtKB and BioDB. Moara consists of the following components: [1] MySQL Databases: [a] Name [b] Author [c] Status [d] Pubmed Id [e] Comments [2] Java libraries and Methods: [a] Moara [b] Wordtokens [c] NER [d] Sentiment [e] NER Categorie [f] Annotation [g] Extractor [h] Tools and scripts *The source code for this application is covered under GPL and can be used for any purpose. However, it is advisable to contact the source/maintainer. Features: [1] Supports Gene/Proteins extraction from UniProtKB, RefSeq, NR, TAIR and UniProtKB/Swiss-Prot databases. [2] Extracts domain and species, gene name, protein name and synonyms. [3] Domain, Species and Gene/Protein name extraction. [4] Supports normalization of gene and protein mention across 3 different versions of UniProtKB and RefSeq, as well as mentions across different species. [5] Provides a comprehensive list of identifiers. [6] Involves in the development of synonym mapping. [7] Allows extraction of generic and organism specific ID’s and functional annotation from EMBL, UniProtKB and UniProtKB/Swiss-Prot databases. [8] Lists domain information of genes. *There is no commercial support/customization services provided by this software. *There is no database maintained for loading annotation data. Users are to manually import the database entries. *The source code for this application is covered under GPL and can be used for any purpose. However, it is advisable to contact the source/maintainer. *No warranty is provided. *This product is provided under a licensed and published open source GPLv2 license, This license does

System Requirements For Moara:

Minimum: OS: Windows 7 64-bit Processor: Intel Pentium 4 3.6GHz Memory: 1 GB RAM Graphics: Microsoft DirectX 9.0c or greater, 128MB video memory DirectX 9.0c or greater, 128MB video memory Hard Drive: 10 GB available space Sound Card: DirectX 9.0c-compatible sound card Additional Notes: Mouse required Broadcast or Stream Network: High-speed Internet connection with a minimum of 512Kb/s upload