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To validate the approach to the prediction of metabolic function associated with a TR, we analyzed ten transcriptional regulators with known functions and effectors utilizing our software named Function Discovery V1.0.

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FAST-NMR utilizes our CPASS software and database to assign a function based on a similarity in the structure and sequence of ligand binding sites between proteins of known and unknown function.

Funding for manual annotation is limited and therefore we have explored a community annotation approach, which utilizes our annotation software and analysis pipelines.

Electrophysiological signals were amplified via a multichannel differential amplifier (Biomedical Engineering, Thornwood, NY) and were acquired utilizing the software developed by Dr. Vadym Gnatkovsky in our laboratory (ELPHO™).

The proliferation rate was determined quantitatively by utilizing NIH Image J software (public domain software).

Miscellaneous-coding RNAs were identified using the Rfam database [72] utilizing the INFERNAL software package [73].

All analyses were performed utilizing the SPSS software package (Version 11.5, SPSS Inc., Chicago, IL).

The captured fluorescence images are analyzed by utilizing ImageJ software.

Formative evaluations were performed with representative students utilizing Morae software.

The authentic biaxial failure stress was obtained utilizing numerical software.

This approach was efficient in utilizing these software packages for automated and systematic FE model updating.

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