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Conservation of Protein Domains Over Different Proteins

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Protein domains are small structurally independent units that are part of a single amino acid chain. Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
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Mass Spectrometry-Based Proteomics Analyses Using the OpenProt Database to Unveil Novel Proteins Translated from Non-Canonical Open Reading Frames

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Investigating heterogeneous protein annotations toward cross-corpora utilization.

Yue Wang¹, Jin-Dong Kim, Rune Saetre

¹Department of Computer Science, School of Information Science and Technology, University of Tokyo, Tokyo, Japan. wangyue@is.s.u-tokyo.ac.jp

BMC Bioinformatics

|December 10, 2009

Summary

Inconsistent gene and protein annotations across biomedical corpora significantly degrade named entity recognition (NER) performance. Addressing annotation differences in boundaries, scope, distribution, and overlap can prevent performance drops.

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Area of Science:

Bioinformatics
Natural Language Processing
Computational Biology

Background:

Increasing use of corpora for biological text analysis.
Development of numerous named entity recognition (NER) systems.
Lack of consensus on biomedical named entity annotation leads to incompatible resources.

Purpose of the Study:

Investigate sources of incompatibility in gene and protein annotations across corpora.
Quantify the impact of annotation heterogeneity on NER performance.
Identify factors contributing to annotation inconsistencies.

Main Methods:

Explored annotation incompatibilities in GENIA, GENETAG, and AIMed corpora.
Quantitatively measured performance decline in NER using integrated vs. pure data.
Qualitatively analyzed annotation differences through experiments.

Main Results:

Integrating heterogeneous annotations caused significant F-score drops (up to 12%) in protein mention recognition.
Incompatibilities stem from boundary annotation, entity scope, distribution, and overlap.
These issues can be mitigated by carefully considering annotation aspects.

Conclusions:

Analysis highlights key similarities and dissimilarities in gene/protein corpora.
Improved understanding of corpus differences enhances evaluation of protein recognition systems.