1 / 14

Entity Summaries

Entity Summaries. Jing Jiang and Xu Lin BeeSpace Programmers’ Meeting Sept. 6, 2006. A quick review of the NER component. Use two types of information to make a prediction Word features and word surface features E.g. p53, XXXless Contextual features E.g. XXX expression, XXX mutants

fuller-santiago
Télécharger la présentation

Entity Summaries

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Entity Summaries Jing Jiang and Xu Lin BeeSpace Programmers’ Meeting Sept. 6, 2006

  2. A quick review of the NER component • Use two types of information to make a prediction • Word features and word surface features • E.g. p53, XXXless • Contextual features • E.g. XXX expression, XXX mutants • Prediction of the same word/phrase is context-sensitive

  3. Examples of Some Ambiguous Gene Names • foraging • We assayed response decrement for natural and mutant rover and sitter alleles of the foraging (for) gene that encodes a Drosophila PKG. (FN) • Hybrid disadvantage in the larval foraging behaviour of the two neotropical species of Drosophila pavani and Drosophila gaucha… (TN)

  4. Examples of Some Ambiguous Gene Names • ss • …SmZF1 binds both ds and ss DNA oligonucleotides,… (TN) • Coexpression of Ss and Tgo in Drosophila SL2 cells… (TP) • The origin of germline-limited chromosomes (Ks) as descendants of somatic chromosomes (Ss) and their… (FP)

  5. Examples of Some Ambiguous Gene Names • black • The purpose of this study was to investigate the black gene, and protein,… (FN) • …beta-alanine biosynthesis is regulated by black. (FN) • Screening a cDNA library prepared from silk-producing glands of the black widow spider,… (TN)

  6. Examples of Some Ambiguous Gene Names • clock • …a novel fitness-related phenotype may be linked to noncircadian expression of clock genes in the ovaries. (TP) • …mPer1 could operate in the adaptation of the circadian clock of nocturnal mice to… (TN)

  7. Examples of Some Ambiguous Gene Names • ERG • To establish the predicted existence of a Drosophila gene in the erg subfamily and… (FN) • The ERG analysis of the norpA mutants suggests that… (TN) • Here we show that the electroretinogram (ERG), the extracellular recording…(FP)

  8. Examples of Some Ambiguous Gene Names • pdf • PDF is coded in a precursor protein together with another neuropeptide… (TP) • …the Drosophila brain that express the period (per) and pigment dispersing factor (pdf) genes play… (TP)

  9. Old System with Keyword Search Use synonym list from FlyBase, to increase recall String match in the whole abstract

  10. New System with NER Will be replaced by an automated normalizer if there is String match only in the tagged gene mentions, to increase precision

  11. Changes with integration of NER • Recall • Tokenization • Keyword match (whole abstract => gene mentions) • Synonym list • Precision • Exact match => exact match but allowing crossing tag boundary

  12. Example • Query: ABC-a • Without NER: match all 4 cases • With NER: not match the second case xxxxxxxxxxxxxx<GENE>ABCa</GENE> gene xxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxx ABCa xxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxx<GENE>ABC</GENE> a encodes xxxxxxxxxxxx xxx<GENE> gene ABCa</GENE> xxxxxxxxxxxxxxx

  13. Effects of NER on Gene Summarizer • FP  TN (increase precision) • …mPer1 could operate in the adaptation of the circadian clock of nocturnal mice to… (TN) • TP  FN (decrease recall) • …beta-alanine biosynthesis is regulated by black. (FN) • FP  FP (no effect, but not what we want) • Here we show that the electroretinogram (ERG), the extracellular recording…(FP)

  14. A Different Approach • Motivation: to solve a simpler problem than NER because we already know the gene name and its synonyms • Approach: build a classifier that focuses on contextual features to identify FPs • Only use contextual features because the term/phrase already matches a gene name • Need some “good” negative examples (ambiguous gene names) in the training data

More Related