Welcome to the DIEGO Lab

The D.I.E.G.O. lab is focused on advancing knowledge extraction, integration, and analysis methods that empower biomedical discoveries. We are particularly interested in existing knowledge that is embedded in biomedical literature and we are currently working in the areas of:

  • Social media mining
  • Pharmacovigilance
  • Named entity recognition of different biomedical entities (genes, diseases, drugs, and others)
  • Entity identification (normalization)
  • Extraction of binary associations
  • Gene target prioritization
  • New approaches to evaluation and data engineering for text mining
  • Lab Members

    Faculty

    Graciela Gonzalez

    Associate Professor
    Contact

    Email: graciela.gonzalez@asu.edu

    PubMed Bibilography

    Post Doctoral Researchers

    Abeed Sarker

    Research Scholar

    Email: abeed.sarker@asu.edu

    Area of interest

    Social Media Mining
    Natural Language Processing
    Machine Learning

    Current projects

    Mining Social Network Postings for Mentions of Potential Adverse Drug Reactions


    Davy Weissenbacher

    Research Scholar

    Contact

    Email: davy.weissenbacher@asu.edu


    PhD Students

    Amol Bhalla

    Research Specialist

    Contact

    Email: amol.bhalla@asu.edu

    Ehsan Emadzadeh

    Research Assistant

    Contact

    Email: ehsan.emadzadeh@asu.edu

    Neel Mehta

    Research Assistant

    Contact

    Email: neel.mehta@asu.edu

    Azadeh Nikfarjam

    Research Assistant

    Contact

    Email: azadeh.nikfarjam@asu.edu

    Ryan Sullivan

    Research Assistant

    Contact

    Email: ryan.sullivan@asu.edu

    Tasnia Tahsin

    Research Assistant

    Contact

    Email: tasnia.tahsin@asu.edu

    Laura Wojtulewicz

    Research Assistant

    Contact

    Email: laura.wojtulewicz@asu.edu

    Robert Yao

    Research Assistant

    Contact

    Email: robertjames.yao@asu.edu

    Masters Students

    Stephanie Furniss

    Research Assistant

    Karen O'Connor

    Research Assistant

    Sunit Guldas

    Research Assistant

    Graduated Students

    Apurv Patki

    Pranoti Pimpalkhute

    Kanishak Dua

    Robert Leaman

    Nate Sutton

    Jian Yang

    Jang Lee

    Siddhartha Jonnalagadda

    Fabian Spinnenhirn

    Xiaoxiao Wang

    Juan Uribe

    Rachel Ginn

    Research Assistant

    Robert Rivera

    Research Assistant

    Swetha Jayaraman

    Research Assistant

    Tejaswi Upadhyaya

    Research Assistant

    Other Students

    Chris Miller

    Annie Skariah

    Undergraduate Students

    Mark Karlsrud

    Projects

      Current projects



    Abstract

    Drugs undergo extensive testing in animals and clinical trials in humans before they are marketed for widespread use in the population. Pre-market testing produces reasonably high quality information about the efficacy of the drug as a treatment for the condition for which it was approved, but gives a very incomplete picture of the drug's safety. Post-marketing surveillance currently relies mainly on voluntary reporting to the FDA by health care professionals (and recently, patients themselves) through MedWatch, the FDA's safety information and adverse event reporting program. Self-reported patient information captures a valuable perspective that has been found to be of similar quality to that provided by health professionals, and currently it is only captured via the formal MedWatch form. The overarching goal of this application is to deploy the infrastructure needed to explore the value of informal social network postings as a source of "signals" of potential adverse drug reactions soon after the drugs hit the market, paying particular attention at the value such information might have to detect adverse events earlier than currently possible, and to detect effects not easily captured by traditional means. Despite the significant challenge of processing colloquial text, our prototype study in this direction showed promising performance in identifying adverse reactions mentioned in these postings, with significant correlations between the effects mentioned by the public and those documented for the drugs we studied.

    Links

  • Annotation Guidelines
  • View Database Stats
  • Publication Repository
  • Download Stats
  • Publications

  • Portable automatic text classification for adverse drug reaction detection via multi-corpus training. Journal of Biomedical Informatics.
  • Pharmacovigilance from social media: Extraction of adverse drug reaction mentions using sequence labeling with word embedding cluster features.
  • Utilizing social media for pharmacovigilance: A review.
  • Mining Twitter for adverse drug reaction mentions: a corpus and classification benchmark.
  • Mining adverse drug reaction signals from social media: going beyond extraction.
  • Pharmacovigilance on Twitter? Mining Tweets for Adverse Drug Reactions.
  • Phonetic spelling filter for keyword selection in drug mention mining from social media.
  • Towards generating a patient's timeline: Extracting temporal relationships from clinical notes.
  • Pattern Mining for Extraction of mentions of Adverse Drug Reactions from User Comments.
  • Towards generating a patient's timeline: Extracting temporal relationships from clinical notes.

  • More project information
  • Abstract

    A corpus has been created to try to help improve drug-gene interaction extraction methods.

    Links

  • More Information
  • Publications

    Abstract

    BANNER is a named entity recognition system, primarily intended for biomedical text. It is a machine-learning system based on conditional random fields and contains a wide survey of the best features in recent literature on biomedical named entity recognition (NER). BANNER is portable and is designed to maximize domain independence by not employing semantic features or rule-based processing steps. It is therefore useful to developers as an extensible NER implementation, to researchers as a standard for comparing innovative techniques, and to biologists requiring the ability to find novel entities in large amounts of text.

    Team

  • Robert Leaman
  • Zachary Slocum
  • Links

  • More Information
  • Publications

    Abstract

    Project details...

    Team

  • Davy Weissenbacher
  • team member 2..
  • Links

  • Toponym Resolution Resources
  • Publications

    Abstract

    The aim is to be able to set a target disease and obtain a list of genes possible related to the target disease. The genes will be ranked according to a method that involves known evidence and the role of the gene in a network of interrelated genes. The process starts by obtaining a set of seed genes which are known to be related to the disease. These genes will be obtained from the CBioC database, and you will be able to edit the list before continuing to the next step. If you want you can leave the disease box empty and you can type your own set of seed genes.

    Team

  • Neel Mehta
  • Laura Wojtulewicz
  • Tasnia Tahsin
  • Links

  • More Information
  • Publications

      Completed projects



    Abstract

    Mehta Neel B. A comparative analysis of knowledge based gene prioritization methods: Is the supply greater than the demand, 9th Annual Rocky Mountain Bioinformatics Conference 2011, Aspen, Colorado, USA

    Team

  • Neel Mehta
  • Links

  • Poster Abstract
  • Publications

    Publications

    2007200820092010201120122013201420152016

    2016

    Abeed Sarker, Karen O'Connor, Rachel Ginn, Matthew Scotch, Karen Smith, Dan Malone, Graciela Gonzalez. Social Media Mining for Toxicovigilance: Automatic Monitoring of Prescription Medication Abuse from Twitter. Drug Safety. 2016 Mar;39(3):231-40. doi: 10.1007/s40264-015-0379-4

    Abeed Sarker, Azadeh Nikfarjam, Graciela Gonzalez. Social Media Mining Shared Task Workshop. Pacific Symposium on Biocomputing. 2016.

    Ryan Sullivan, Abeed Sarker, Karen O'Connor, Amanda Gooding, Mark Karlsrud, Graciela Gonzalez. Finding Potentially Unsafe Nutritional Supplements from User Reviews With Topic Modeling. Pacific Symposium on Biocomputing. 2016.

    Michael J Paul, Abeed Sarker, John S Brownstein, Azadeh Nikfarjam, Matthew Scotch, Karen L Smith, Graciela Gonzalez. Social Media Mining for Public Health Monitoring and Surveillance. Pacific Symposium on Biocomputing. 2016.


    2015

    Azadeh Nikfarjam, Abeed Sarker, Karen O'Connor, Rachel Ginn, Pranoti Pimpalkhute, Graciela Gonzalez. Pharmacovigilance from social media: Extraction of adverse drug reaction mentions using sequence labeling with word embedding cluster features. Journal of the American Medical Informatics Association.

    Abeed Sarker, Rachel Ginn, Azadeh Nikfarjam, Karen O'Connor, Karen Smith, Swetha Jayaraman, Tejaswi Upadhaya, Graciela Gonzalez. Utilizing social media data for pharmacovigilance: A review. Journal of Biomedical Informatics. 54 (2015) 202-212.

    Abeed Sarker, Azadeh Nikfarjam, Davy Weissenbacher, Graciela Gonzalez. DIEGOLab: An Approach for Message-level Sentiment Classification in Twitter. Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015), pages 510-514, Denver, Colorado, June 4-5, 2015.

    Davy Weissenbacher, Tasnia Tahsin, Rachel Beard, Mari Firago, Robert Rivera, Matthew Scotch, Graciela Gonzalez. Knowledge-driven geospatial location resolution for phylogeographic models of virus migration, Bioinformatics (2015) 31 (12): i348-i356. doi: 10.1093/bioinformatics/btv259.

    Tasnia Tahsin, Davy Weissenbacher, Robert Rivera, Rachel Beard, Mari Firago, Garrick Wallstrom, Matthew Scotch, Graciela Gonzales. A high-precision rule-based extraction system for expanding geospatial metadata in GenBank records.DOI: http://dx.doi.org/10.1093/jamia/ocv172 ocv172 First published online: 17 January 2016.


    2014

    Rachel Ginn, Pranoti Pimpalkhute, Azadeh Nikfarjam, Apurv Patki, Karen O'Connor, Abeed Sarker, Karen Smith and Graciela Gonzalez. Mining Twitter for Adverse Drug Reaction Mentions: A Corpus and Classification Benchmark. In proceedings of the Fourth Workshop on Building and Evaluating Resources for Health and Biomedical Text Processing (BioTxtM2014). May, 2014. Reykjavik, Iceland.

    Paradoxical Impact Of Widowhood On Incidence Of Dementia In Subjects With Mild Cognitive Impairment

    Laura B. Wojtulewicz, Keith Woodruffemail, Cynthia M. Stonnington, Dona E.C. Locke, Joseph G. Hentz, Amylou C. Dueck, Yonas E. Geda, Richard J. Caselli. Paradoxical Impact Of Widowhood On Incidence Of Dementia In Subjects With Mild Cognitive Impairment.

    Text Classification towards Detecting Misdiagnosis of an Epilepsy Syndrome in a Pediatric Population

    Ryan Sullivan, Robert Yao, Randa Jarrar, Jeffrey Buchhalter, Graciela Gonzalez. Text Classification towards Detecting Misdiagnosis of an Epilepsy Syndrome in a Pediatric Population.

    Mining Adverse Drug Reaction Signals from Social Media: Going Beyond Extraction

    Apurv Patki, Abeed Sarker, Pranoti Pimpalkhute, Azadeh Nikfarjam, Rachel Ginn, Karen O'Connor, Karen Smith, Graciela Gonzalez. Mining adverse drug reaction signals from social media: going beyond extraction. In: Proceedings of BioLinkSig 2014; 2014.

    Abeed Sarker and Graciela Gonzalez. Portable automatic text classification for adverse drug reaction detection via multi-corpus training. Journal of Biomedical Informatics. 53 (2015) 196–207.

    Karen O'Connor, Azadeh Nikfarjam, Rachel Ginn, Pranoti Pimpalkhute, Abeed Sarker, Karen Smith, Graciela Gonzalez. Pharmacovigilance on Twitter? Mining Tweets for Adverse Drug Reactions. AMIA Annual Symposium 2014.

    Phonetic spelling filter for keyword selection in drug mention mining from social media.

    P Pimpalkhute, A Patki, A Nikfarjam, G Gonzalez. "Phonetic spelling filter for keyword selection in drug mention mining from social media." AMIA TBI Summit (2014).


    2013

    Evaluating the Use of Empirically Constructed Lexical Resources for Named Entity Recognition

    Siddhartha Jonnalagadda, Trevor Cohen, Stephen Wu, Hongfang Liu, and Graciela Gonzalez. 2013.
    Evaluating the Use of Empirically Constructed Lexical Resources for Named Entity Recognition. In Proceedings of CSCT 2013, pages 23-33.

    Using empirically constructed Lexical Resources for named entity Recognition

    Jonnalagadda S, Cohen T, Wu S, Liu H, Gonzalez G.
    Using Empirically Constructed Lexical Resources for Named Entity Recognition. Biomed Inform Insights. 2013.

    Text and data mining for biomedical discovery-session introduction.

    Authors: G Gonzalez, KB Cohen, CS Greene, MG Kann, R Leaman, N Shah, J Ye.

    Towards generating a patient's timeline: Extracting temporal relationships from clinical notes

    Azadeh Nikfarjam , Ehsan Emadzadeh , Graciela Gonzalez.
    Towards generating a patient's timeline: Extracting temporal relationships from clinical notes, Journal of Biomedical Informatics, 46, p.S40-S47, December, 2013


    2012

    A Hybrid system for emotion extraction from suicide notes

    Azadeh Nikfarjam, Ehsan Emadzadeh, Graciela Gonzalez.

    Proposed Ontology for Seizure and Epilepsy.

    Robert Yao, Jeffrey Buchhalter, Graciela Gonzalez

    Text and data mining for biomedical discovery.

    GRACIELA Gonzalez, KEVIN BRETONNEL Cohen, CASEY S Greene, U Hahn, MARICEL G Kann, ROBERT Leaman, NIGAM Shah, JIEPING Ye.

    Temporal Relationship Extraction from Clinical Notes Using SVM and Graph Reasoning

    Nikfarjam, Azadeh, et al.
    "Temporal relationship extraction from clinical-notes using SVM and graph reasoning." Proceedings of. 2012.

    Enhancing clinical concept extraction with distributional semantics

    Jonnalagadda S, Cohen T, Wu S, et al.
    Enhancing clinical concept extraction with distributional semantics. J Biomed Inform 2012;45:129–40.

    Automatic approaches for gene-drug interaction extraction from biomedical text: corpus and comparative evaluation

    Nate Sutton, Laura Wojtulewicz, Neel Mehta, Graciela Gonzalez.


    2011

    Towards integrative gene prioritization in Alzheimer's disease.

    Lee JH, Gonzalez GH.
    Towards integrative gene prioritization in Alzheimer's disease. Pacific Symposium on Biocomputing, Hawaii, USA: World Scientific, 2011:4–13.

    Pattern Mining for Extraction of mentions of Adverse Drug Reactions from User Comments.

    Nikfarjam, Azadeh and Graciela H. Gonzalez.
    "Pattern Mining for Extraction of mentions of Adverse Drug Reactions from User Comments." AMIA Annual Symposium Proceeding, 2011.

    Applications for a Translational Biomedical Ontology Model.

    Robert Yao, Graciela Gonzalez.

    Biomedical Informatics in Translational Research

    Biomedical Informatics in Translational Research, Hai Hu, Richard J. Mural, Michael N. Liebman (Eds.). Artech House (2008).

    Double layered learning for biological event extraction from text

    Ehsan Emadzadeh, Azadeh Nikfarjam, Graciela Gonzalez.
    Double layered learning for biological event extraction from text, Proceedings of the BioNLP Shared Task 2011 Workshop, p.153-154, June 24-24, 2011, Portland, Oregon

    The GNAT library for local and remote gene mention normalization

    Hakenberg J., et al.
    The GNAT library for local and remote gene mention normalization. Bioinformatics 2011;27:2769-2771.

    Benchmarking of the 2010 BioCreative Challenge III text-mining competition by the BioGRID and MINT interaction databases

    Martin Krallinger, Miguel Vazquez, Florian Leitner, David Salgado, Andrew Chatr-aryamontri, Andrew Winter, Livia Perfetto, Leonardo Briganti, Luana Licata, Marta Iannuccelli, Luisa Castagnoli, Gianni Cesareni, Mike Tyers, Gerold Schneider, Fabio Rinaldi, Robert Leaman, Graciela Gonzalez, Sergio Matos, Sun Kim, W Wilbur, Luis Rocha, Hagit Shatkay, Ashish V Tendulkar, Shashank Agarwal, Feifan Liu, Xinglong Wang, Rafal Rak, Keith Noto, Charles Elkan, Zhiyong Lu, Rezarta Dogan, Jean-Fred Fontaine, Miguel A Andrade-Navarro, Alfonso Valencia

    The Protein-Protein Interaction tasks of BioCreative III: classification/ranking of articles and linking bio-ontology concepts to full text

    Krallinger M, Vazquez M, Leitner F, Salgado D, Chatr-Aryamontri A, Winter A, Perfetto L, Briganti L, Licata L, Iannuccelli M, et al.
    The protein-protein interaction tasks of BioCreative III: classification/ranking of articles and linking bio-ontology concepts to full text. BMC Bioinformatics 2011;12 Suppl. 8:S3.

    Evaluating Distributional Semantic and Feature Selection for Extracting Relationships from Biological Text

    Ehsan Emadzadeh, Siddhartha Jonnalagadda, Graciela Gonzalez.

    The DIEGO Lab Graph Based Gene Normalization System

    Ryan Sullivan, Robert Leaman, Graciela Gonzalez.

    Enhancing phylogeography by improving geographical information from GenBank

    Scotch M, Sarkar IN, Mei C, Leaman R, Cheung KH, Ortiz P, Singraur A, Gonzalez G.
    Enhancing phylogeography by improving geographical information from GenBank. J Biomed Inform 2011, 44(1):S44-47.


    2010

    A Distributional Semantics Approach to Simultaneous Recognition of Multiple Classes of Named Entities

    Jonnalagadda, Siddhartha, et al.
    "A distributional semantics approach to simultaneous recognition of multiple classes of named entities." Computational Linguistics and Intelligent Text Processing. Springer Berlin Heidelberg, 2010. 224-235.

    Parse tree database for information extraction

    L. Tari et al,, 2009.
    Parse Tree Database for Information Extraction, IEEE TRANSACTIONS ON KNOWLEDGE & DATA ENGINEERING

    BioSimplify: an open source sentence simplification engine to improve recall in automatic biomedical information extraction.

    Jonnalagadda, Siddhartha, and Graciela Gonzalez.
    "BioSimplify: an open source sentence simplification engine to improve recall in automatic biomedical information extraction." AMIA Annual Symposium Proceedings. Vol. 2010. American Medical Informatics Association, 2010.

    Can distributional statistics aid clinical concept extraction?

    Jonnalagadda, Siddhartha, and Graciela Gonzalez.
    "Can distributional statistics aid clinical concept extraction." Proceedings of the 2010 i2b2/VA Workshop on Challenges in Natural Language Processing for Clinical Data. Boston, MA, USA: i2b2. 2010.

    Sentence simplification aids protein-protein interaction extraction.

    Jonnalagadda, Siddhartha, and Graciela Gonzalez.
    "Sentence simplification aids protein-protein interaction extraction." arXiv preprint arXiv:1001.4273(2010).

    GenerIE: Information extraction using database queries

    Luis Tari, Phan Huy Tu, Jörg Hakenberg, Yi Chen, Tran Cao Son, Graciela Gonzalez, Chitta Baral.

    Efficient extraction of protein-protein interactions from full-text articles.

    Hakenberg, Jörg, et al.
    "Efficient extraction of protein-protein interactions from full-text articles." IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) 7.3 (2010): 481-494.

    Towards internet-age pharmacovigilance: extracting adverse drug reactions from user posts to health-related social networks.

    Leaman, Robert, Laura Wojtulewicz, Ryan Sullivan, Annie Skariah, Jian Yang, and Graciela Gonzalez.
    "Towards internet-age pharmacovigilance: extracting adverse drug reactions from user posts to health-related social networks."Proceedings of the 2010 workshop on biomedical natural language processing. Association for Computational Linguistics, 2010.

    A comparative study on Measure of Semantic Relatedness function

    Emadzadeh, Ehsan, Azadeh Nikfarjam, and Saravanan Muthaiyah.
    "A comparative study on Measure of Semantic Relatedness function." Computer and Automation Engineering (ICCAE), 2010 The 2nd International Conference on. Vol. 1. IEEE, 2010.

    A top-down approach for finding interaction detection methods

    Leaman R, Sullivan R, Gonzalez G.
    Proceedings of the BioCreative III workshop; Bethesda MA, USA. CNIO; 2010. A top-down approach for finding interaction detection methods; pp. 99–103.

    Learning Materials Recommendation Using a Hybrid Recommender System with Automated Keyword Extraction.

    Emadzadeh, Ehsan, et al.
    "Learning Materials Recommendation Using a Hybrid Recommender System with Automated Keyword Extraction." World Applied Sciences Journal 9.11 (2010): 1260-1271.

    NEMO: Extraction and normalization of organization names from PubMed affiliation strings.

    Jonnalagadda, Siddhartha, and Philip Topham.
    "NEMO: Extraction and normalization of organization names from PubMed affiliation strings." Journal of biomedical discovery and collaboration 5 (2010): 50.

    Quality attributes and classification of schema matchers.

    Emadzadeh, Ehsan, Saravanan Muthaiyah, and Azadeh Nikfarjam.
    "Quality attributes and classification of schema matchers." Computer Engineering and Applications (ICCEA), 2010 Second International Conference on. Vol. 2. IEEE, 2010.

    Text mining approaches for stock market prediction.

    Nikfarjam, Azadeh, Ehsan Emadzadeh, and Saravanan Muthaiyah.
    "Text mining approaches for stock market prediction." Computer and Automation Engineering (ICCAE), 2010 The 2nd International Conference on. Vol. 4. IEEE, 2010.

    Incremental information extraction using relational databases

    Tari, L. Tu, P. Hakenberg, J. Chen, Y. Son, T. Gonzalez, G. Baral.
    “Incremental Information Extraction Using Relational Databases”. Knowledge and Data Engineering, IEEE Transactions on Issue:99 , pp 25-35, 28 October 2010


    2009

    Enabling Recognition of Diseases in Biomedical Text with Machine Learning: Corpus and Benchmark

    Robert Leaman, Christopher Miller, Graciela Gonzalez (2009)
    Enabling Recognition of Diseases in Biomedical Text with Machine Learning: Corpus and Benchmark, 82-89. In 2009 Symposium on Languages in Biology and Medicine.

    Integrating querying and retrieval for biomedical information extraction

    Tari L, Tu PH, Hakenberg J, et al.
    Integrating querying and retrieval for biomedical information extraction. ICDE. 2009

    Towards effective sentence simplification for automatic processing of biomedical text.

    Jonnalagadda, Siddhartha, et al.
    "Towards effective sentence simplification for automatic processing of biomedical text." Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers. Association for Computational Linguistics, 2009.

    Molecular event extraction from Link Grammar parse trees

    Hakenberg,J. et al. (2009)
    Molecular event extraction from link grammar parse trees. In Proceedings of the BioNLP 2009 Workshop Companion Volume for Shared Task, Association for Computational Linguistics, pp. 86–94.

    Towards automatic extraction of social networks of organizations in PubMed abstracts.

    Jonnalagadda, Siddhartha, Philip Topham, and Graciela Gonzalez.
    "Towards automatic extraction of social networks of organizations in PubMed abstracts."Bioinformatics and Biomedicine Workshop, 2009. BIBMW 2009. IEEE International Conference on. IEEE, 2009.

    ONER: Tool for Organization Named Entity Recognition from Affiliation Strings in PubMed Abstracts.

    Jonnalagadda, Siddhartha, Philip Topham, and Graciela Gonzalez.
    "ONER: Tool for Organization Named Entity Recognition from Affiliation Strings in PubMed Abstracts." The 3rd International Symposium on Languages in Biology and Medicine, Jeju Island, South Korea. 2009.

    Querying Parse Tree Database of Medline Text to Synthesize User-Specific Biomolecular Networks.

    Tari L, Hakenberg J, Gonzalez G, Baral C.
    Querying parse tree database of MEDLINE text to synthesize user-specific biomolecular networks. In: Pacific symposium on biocomputing; 2009. p. 87–98.


    2008

    BANNER: an executable survey of advances in biomedical named entity recognition.

    Leaman, Robert, and Graciela Gonzalez.
    "BANNER: an executable survey of advances in biomedical named entity recognition." Pacific Symposium on Biocomputing. Vol. 13. 2008.

    Generalized text extraction from molecular biology text using parse tree database querying

    Phan Huy Tu, Chitta Baral, Yi Chen, and Graciela Gonzalez. 2008.
    Generalized text extraction from molecular biology text using parse tree database querying. Technical Report TR-08-004, Arizona State University

    GeneRanker: An Online System for Predicting Gene-Disease Associations for Translational Research

    Gonzalez, G., Uribe, J.C., Armstrong, B., McDonough, W. & Berens, M.E.
    GeneRanker: an online system for predicting gene-disease associations for translational research. Summit on Translat. Bioinforma. 2008, 26–30 (2008).

    Inter-species normalization of gene mentions with GNAT

    Hakenberg J, Plake C, Leaman R, Schroeder M, Gonzales G.
    Inter-species normalization of gene mentions with GNAT. Bioinformatics 2008, 24(16):i126-i132.

    Glycoinformatics: Text Mining Lectin and Glycan Interactions in Bioprocesses

    Samli, Kausar N., et al.
    "Glycoinformatics: Text Mining Lectin and Glycan Interactions in Bioprocesses." GLYCOBIOLOGY. Vol. 18. No. 11. JOURNALS DEPT, 2001 EVANS RD, CARY, NC 27513 USA: OXFORD UNIV PRESS INC, 2008.


    2007

    CBioC: beyond a prototype for collaborative annotation of molecular interactions from the literature

    Chitta Baral, Graciela Gonzalez, Anthony Gitter, Craig Teegarden, Amanda Zeigler.
    CBioC: beyond a prototype for collaborative annotation of molecular interactions from the literature. In: Computational systems bioionformatics conference, 2007.

    Integrating knowledge extracted from biomedical literature: normalization and evidence statements for interactions.

    Gonzalez, Graciela, et al.
    "Integrating knowledge extracted from biomedical literature: normalization and evidence statements for interactions." Proceedings of the Second BioCreative Challenge Workshop-Critical Assessment of Information Extraction in Molecular Biology. 2007.

    Mining Gene-Disease relationships from Biomedical Literature:

    Gonzalez, G., et al.
    Mining Gene-Disease relationships from Biomedical Literature: Incorporating Interactions, Connectivity, Confidence, and Context Measures. in Pacific Symposium in Biocomputing. 2007. Maui, Hawaii.

    Passage Relevancy Through Semantic Relatedness.

    L. Tari, P. H. Tu, B. Lumpkin, R. Leaman, G. Gonzalez, and C. Baral.
    “Passage relevancy through semantic relatedness,” in Proceedings of the Sixteenth Text REtrieval Conference, TREC 2007, 2007.

    Passage relevancy through semantic similarity

    Tari L, Tu P, Lumpkin B, Leaman R, Gonzalez G, Baral C.
    Passage relevancy through semantic similarity. In The Sixteenth Text REtrieval Conference (TREC 2007) Proceedings 2007.

    Mining gene-disease relationships from biomedical literature: weighting protein-protein interactions and connectivity measures

    Gonzalez G, Uribe JC, Tari L, Brophy C, Baral C.
    Mining gene-disease relationships from biomedical literature: weighting protein-protein interactions and connectivity measures. Pac Symp Biocomput 2007, 28-39.

    Web service orchestration for bioinformatics systems: challenges and current workflow definition approaches

    Gonzalez, G.; Balasooriya, J.
    "Web Service Orchestration for Bioinformatics Systems: Challenges and Current Workflow Definition Approaches," Web Services, 2007. ICWS 2007. IEEE International Conference on , vol., no., pp.1226,1227, 9-13 July 2007


    Downloads

    BioSimplify Project

  • The source code for this project can be accessed here: InformationExtraction_src.zip

  • ADR PROJECT

    1. Publication specific downloads

    2. Twitter Annotated Corpus

        The Diego Lab provide a manually annotated corpus for drugs related comments to train models to mine the Twitter microblogging platform for ADRs (Adverse Drug Reaction).

    3. Adverse Drug Reactions (ADRs)

    Medication Abuse Monitoring using Twitter

    1. Drug Abuse Corpus (initial)

        Binary annotations indicating medication abuse..

    Contact Us

    Address

    Mayo Clinic, Samuel C. Johnson Research Bldg
    13212 East Shea Boulevard
    Scottsdale, Arizona 85259 United States

    Phone

    (480) 884-0220

    Fax

    480-884-0239