LINNAEUS: A species name identification system for biomedical literature

Gerner, Martin; Nenadić, Goran; Bergman, Casey M.

doi:10.1186/1471-2105-11-85

Cited by 276 publications

(266 citation statements)

References 44 publications

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“…State-of-the-art recognizers can be used to tag organisms (Gerner et al 2010), chemical entities (Jessop et al 2011) and genes, proteins and other biological entities (Settles 2005). The vocabulary on AMPs, eg derived from the UniProt knowledge base (Magrane and Consortium 2011) and antibiotics lexicon derived from the ARDB database (Liu and Pop 2009) and the antibiotics list in Wikipedia (Wikipedia 2012), can support the pattern matching of AMP mentions and further development of suitable recognizers.…”

Section: Data Screening and Processingmentioning

confidence: 99%

New trends in peptide-based anti-biofilm strategies: a review of recent achievements and bioinformatic approaches

2012

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Antimicrobial peptides (AMPs) have a broad spectrum of activity and unspecific mechanisms of action. Therefore, they are seen as valid alternatives to overcome clinically relevant biofilms and reduce the chance of acquired resistance. This paper reviews AMPs and anti-biofilm AMP-based strategies and discusses ongoing and future work. Recent studies report successful AMP-based prophylactic and therapeutic strategies, several databases catalogue AMP information and analysis tools, and novel bioinformatics tools are supporting AMP discovery and design. However, most AMP studies are performed with planktonic cultures, and most studies on sessile cells test AMPs on growing rather than mature biofilms. Promising preliminary synergistic studies have to be consubstantiated and the study of functionalized coatings with AMPs must be further explored. Standardized operating protocols, to enforce the repeatability and reproducibility of AMP anti-biofilm tests, and automated means of screening and processing the ever-expanding literature are still missing.

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Section: Data Screening and Processingmentioning

confidence: 99%

New trends in peptide-based anti-biofilm strategies: a review of recent achievements and bioinformatic approaches

2012

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“…EVEX 17 extends the TEES event extraction system and is used to extract additional features for event extraction of GENIA Event Extraction task. Other text-mining advances include biological relationship extraction such as gene-disease interactions, 18 named entity recognition (gene/protein name, 19 organisms, 20 and diseases, 21 etc.). Current web-based text mining techniques for PTM information extraction include RLIMS-P, 22 RLIMS-P 2.0, 23 eFIP 24 and MinePhos, 25 RLIMS-P 22 is the¯rst tool for PTM information extraction.…”

Section: Introductionmentioning

confidence: 99%

MPTM: A tool for mining protein post-translational modifications from literature

Sun

Wang

2017

J. Bioinform. Comput. Biol.

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Due to the importance of post-translational modi¯cations (PTMs) in human health and diseases, PTMs are regularly reported in the biomedical literature. However, the continuing and rapid pace of expansion of this literature brings a huge challenge for researchers and database curators. Therefore, there is a pressing need to aid them in identifying relevant PTM information more e±ciently by using a text mining system. So far, only a few web servers are available for mining information of a very limited number of PTMs, which are based on simple pattern matching or pre-de¯ned rules. In our work, in order to help researchers and database curators easily¯nd and retrieve PTM information from available text, we have developed a text mining tool called MPTM, which extracts and organizes valuable knowledge about 11 common PTMs from abstracts in PubMed by using relations extracted from dependency parse trees and a heuristic algorithm. It is the¯rst web server that provides literature mining service for hydroxylation, myristoylation and GPI-anchor. The tool is also used to¯nd new publications on PTMs from PubMed and uncovers potential PTM information by large-scale text analysis. MPTM analyzes text sentences to identify protein names including substrates and proteininteracting enzymes, and automatically associates them with the UniProtKB protein entry. To facilitate further investigation, it also retrieves PTM-related information, such as human diseases, Gene Ontology terms and organisms from the input text and related databases. In addition, an online database (MPTMDB) with extracted PTM information and a local MPTM Lite package are provided on the MPTM website. MPTM is freely available online at

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“…The evaluated systems include LINNEAUS (Gerner et al, 2010), BANNER, Stanford SUTime (Chang and Manning, 2012) and GeoNamer. LINNEAUS, BAN-NER and Stanford SUTime are widely-used, state-of-the-art open source NER systems for recognition of species, gene and temporal expressions respectively.…”

Section: Development Of Automated Location Taggermentioning

confidence: 99%

“…Similar methods have been applied to disease names (Doğan & Lu, 2012b;Kang et al, 2012;Névéol et al, 2009) and species names (Gerner et al, 2010;Wei et al, 2012b), and the MetaMap program is used to locate and identify concepts from the UMLS MetaThesaurus Bodenreider, 2004).…”

Section: Introductionmentioning

confidence: 99%

Proceedings of BioNLP 2014

2014

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IntroductionThe first day of the BioNLP 2014 workshop continues following the course set by the first ACL workshop on Natural Language Processing in the Biomedical Domain that was held in 2002: BioNLP 2014 provides a venue for exploring challenges and techniques in processing biomedical language and brings together researchers from computational linguistics and biomedical informatics. The submissions to the first day of 2014 workshop organized by SIGBioMed were traditionally very strong and continued demonstrating the considerable breadth of research in biomedical language processing. The 2014 workshop has accepted 12 full and short papers for oral presentations and 7 posters. The first day of the workshop features a keynote that expands the scope of BioNLP beyond its already remarkable breadth The second day of the workshop features a paper submitted to the special track on NLP approaches for assessment of clinical conditions. Kathleen C. Fraser presents the featured talk on using statistical parsing to detect agrammatic aphasia. The track organizers, Thamar Solorio and Yang Liu, serve as discussants.The second day further features an exciting panel that brings together organizers of several shared tasks in biomedical information retrieval and natural language processing. The panel introduces the workshop participants to the long-standing and relatively new community-wide challenges in biomedical and clinical language processing. It also provides an opportunity to discuss the future of the shared tasks in this domain. AcknowledgmentsAs always, we are profoundly grateful to the authors who chose BioNLP as venue for presenting their innovative research. The authors' willingness to share their work through BioNLP consistently makes the workshop noteworthy among the increasing numbers of available venues. We are equally indebted to the program committee members (listed elsewhere in this volume) who produced at least three thorough reviews per paper on a tight review schedule and with an admirable level of insight.iii AbstractZoonotic viruses, viruses that are transmittable between animals and humans, represent emerging or re-emerging pathogens that pose significant public health threats throughout the world. It is therefore crucial to advance current surveillance mechanisms for these viruses through outlets such as phylogeography. Phylogeographic techniques may be applied to trace the origins and geographical distribution of these viruses using sequence and location data, which are often obtained from publicly available databases such as GenBank. Despite the abundance of zoonotic viral sequence data in GenBank records, phylogeographic analysis of these viruses is greatly limited by the lack of adequate geographic metadata. Although more detailed information may often be found in the related articles referenced in these records, manual extraction of this information presents a severe bottleneck. In this work, we propose an automated system for extracting this information using Natural Language Processing (NLP)...

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LINNAEUS: A species name identification system for biomedical literature

Cited by 276 publications

References 44 publications

New trends in peptide-based anti-biofilm strategies: a review of recent achievements and bioinformatic approaches

New trends in peptide-based anti-biofilm strategies: a review of recent achievements and bioinformatic approaches

MPTM: A tool for mining protein post-translational modifications from literature

Proceedings of BioNLP 2014

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