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Employing machine learning for reliable miRNA target identification in plants

Ashwani Jha and Ravi Shankar*

Author Affiliations

Studio of Computational Biology & Bioinformatics, Biotechnology Division, Institute of Himalayan Bioresource Technology, Council of Scientific & Industrial Research (CSIR), Palampur 176061 (HP), India

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BMC Genomics 2011, 12:636  doi:10.1186/1471-2164-12-636

Published: 29 December 2011

Additional files

Additional file 1:

Performance tests and benchmarking related details. This additional file contains the details about the performance benchmarking and tests done for p-TAREF. In overall six different major tests were done for performance benchmarking.

Format: PDF Size: 277KB Download file

This file can be viewed with: Adobe Acrobat Reader

Open Data

Additional file 2:

miRNA target predictions made on rice transcriptome. This file contains result data on Rice transcriptome specific miRNA targets, with corresponding targeting miRNA, encoded interaction pattern differences and SVR score details.

Format: XLS Size: 4.8MB Download file

This file can be viewed with: Microsoft Excel Viewer

Open Data

Additional file 3:

Expression correlation between miRNAs and targets. The file contains details about the miRNA targets found in Rice transcriptome, along with expression correlation values between the target and targeting miRNA.

Format: XLS Size: 4.5MB Download file

This file can be viewed with: Microsoft Excel Viewer

Open Data

Additional file 4:

miRNA groups and their corresponding functional category enrichments with p-values. miRNA targets in Rice transcriptome were grouped according to the miRNA targeting them and their associated GO functional categories for Molecular function and Biological processes.

Format: PDF Size: 31KB Download file

This file can be viewed with: Adobe Acrobat Reader

Open Data