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1.  Natural Language Processing in aid of FlyBase curators 
BMC Bioinformatics  2008;9:193.
Background
Despite increasing interest in applying Natural Language Processing (NLP) to biomedical text, whether this technology can facilitate tasks such as database curation remains unclear.
Results
PaperBrowser is the first NLP-powered interface that was developed under a user-centered approach to improve the way in which FlyBase curators navigate an article. In this paper, we first discuss how observing curators at work informed the design and evaluation of PaperBrowser. Then, we present how we appraise PaperBrowser's navigational functionalities in a user-based study using a text highlighting task and evaluation criteria of Human-Computer Interaction. Our results show that PaperBrowser reduces the amount of interactions between two highlighting events and therefore improves navigational efficiency by about 58% compared to the navigational mechanism that was previously available to the curators. Moreover, PaperBrowser is shown to provide curators with enhanced navigational utility by over 74% irrespective of the different ways in which they highlight text in the article.
Conclusion
We show that state-of-the-art performance in certain NLP tasks such as Named Entity Recognition and Anaphora Resolution can be combined with the navigational functionalities of PaperBrowser to support curation quite successfully.
doi:10.1186/1471-2105-9-193
PMCID: PMC2375127  PMID: 18410678
2.  Annotation of the Drosophila melanogaster euchromatic genome: a systematic review 
Genome Biology  2002;3(12):research0083.1-83.22.
The recent completion of the Drosophila melanogaster genomic sequence to high quality, and the availability of a greatly expanded set of Drosophila cDNA sequences, afforded FlyBase the opportunity to significantly improve genomic annotations.
Background
The recent completion of the Drosophila melanogaster genomic sequence to high quality and the availability of a greatly expanded set of Drosophila cDNA sequences, aligning to 78% of the predicted euchromatic genes, afforded FlyBase the opportunity to significantly improve genomic annotations. We made the annotation process more rigorous by inspecting each gene visually, utilizing a comprehensive set of curation rules, requiring traceable evidence for each gene model, and comparing each predicted peptide to SWISS-PROT and TrEMBL sequences.
Results
Although the number of predicted protein-coding genes in Drosophila remains essentially unchanged, the revised annotation significantly improves gene models, resulting in structural changes to 85% of the transcripts and 45% of the predicted proteins. We annotated transposable elements and non-protein-coding RNAs as new features, and extended the annotation of untranslated (UTR) sequences and alternative transcripts to include more than 70% and 20% of genes, respectively. Finally, cDNA sequence provided evidence for dicistronic transcripts, neighboring genes with overlapping UTRs on the same DNA sequence strand, alternatively spliced genes that encode distinct, non-overlapping peptides, and numerous nested genes.
Conclusions
Identification of so many unusual gene models not only suggests that some mechanisms for gene regulation are more prevalent than previously believed, but also underscores the complex challenges of eukaryotic gene prediction. At present, experimental data and human curation remain essential to generate high-quality genome annotations.
doi:10.1186/gb-2002-3-12-research0083
PMCID: PMC151185  PMID: 12537572
3.  The Drosophila Genome: So That's What it Looks Like! 
Yeast (Chichester, England)  2000;17(2):154-157.
doi:10.1002/1097-0061(20000630)17:2<154::AID-YEA18>3.0.CO;2-Z
PMCID: PMC2448331  PMID: 10900460

Results 1-3 (3)