Exploring inconsistencies in genome-wide protein function annotations: a machine learning approach

doi:10.1186/1471-2105-8-284

BMC Bioinformatics

Volume 8

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Correspondence

Exploring inconsistencies in genome-wide protein function annotations: a machine learning approach

Carson Andorf¹^,3 , Drena Dobbs²^,3^,4 and Vasant Honavar¹^,3^,4

¹Artificial Intelligence Laboratory, Department of Computer Science, Iowa State University, Ames, Iowa, 50011, USA

²Department of Genetics, Development and Cell Biology, Iowa State University, Ames, Iowa, 50011, USA

³Bioinformatics and Computational Biology Graduate Program, Iowa State University, Ames, Iowa, 50011, USA

⁴Center for Computational Intelligence, Learning, and Discovery, Iowa State University, Ames, Iowa, 50011, USA

author email corresponding author email

BMC Bioinformatics 2007, 8:284doi:10.1186/1471-2105-8-284


Published:	3 August 2007

Additional files

Additional file 1:

Supplementary Table 1: Evidence Codes for AmiGO annotations. A table displaying the Evidence Codes for AmiGO annotations of the mouse protein kinases used in this study.

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Additional file 2:

Supplementary Table 2: AmiGO annotations versus UniProt annotations (with UniProt Evidence). A table comparing the annotations found in the AmiGO server with the annotations found in UniProt.

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Additional file 3:

Supplementary Table 3: AmiGO labels, UniProt labels, and Predicted Labels for each mouse kinase protein. A table comparing the predicted annotations from our three machine learning classifiers with the annotations of AmiGO and UniProt.

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Additional file 4:

Supplementary Data: Machine learning approaches to predict Gene Ontology and/or UniProt Functional labels. The data provided represent the results and performance of all the machine learning approaches used in this study.

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Additional file 5:

Supplementary Table 4: Mouse kinases having a human ortholog. A table displaying the human orthologs for the mouse kinases used in this study. The table also displays the identity between these orthologs.

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Additional file 6:

Supplementary Table 5: Number of mouse kinases having a specified level of sequence identity with their human orthologs. A table displaying the summary statistics of Supplementary Table 4.

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Additional file 7:

Supplementary Note. Because there is only a non-curated reference to the work done on "Rat ISS GO annotations from MGI's mouse gene data," we provide the abstract and a link to the original reference report in this file.

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Additional file 8:

Supplementary Table 6: The UniProt and AmiGO annotations for the rat kinase proteins with mouse orthologs. This table displays the UniProt and AmiGO annotations for rat kinase proteins that were annotated based on a mouse ortholog.

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Additional file 9:

Supplementary Table 7: Distribution of protein classes for human and mouse proteins annotated by AmiGO, UniProt, and HDTree. This table is a representation of the data used in Figure 1 which is a pie chart showing the distribution of human and mouse protein classes based on annotations found in AmiGO, UniProt, and predicted by HDTree.

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