Machine Learning and Deep Learning

Jeyachitra, R. K.; Manochandar, S.

doi:10.1002/9781119785491.ch10

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2024

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Cited by 2 publications

References 61 publications

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Energy-efficient design for green indoor OWC-IoT systems using passive reflective filters and machine learning-assisted quality prediction

Jenila,

Jeyachitra

2024

Telecommun Syst

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Energy-efficient design for green indoor OWC-IoT systems using passive reflective filters and machine learning-assisted quality prediction

Jenila,

Jeyachitra

2024

Telecommun Syst

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Elucidating Electronic Structure Variations in Nucleic Acid-Protein Complexes Involved in Transcription Regulation Using a Tight-Binding Approach

Du,

Liu

2024

Preprint

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Transcription factor (TF) are proteins that regulates the transcription of genetic information from DNA to messenger RNA by binding to a specific DNA sequence. Nucleic acid-protein interactions are crucial in regulating transcription in biological systems. This work presents a quick and convenient method for constructing tight-binding models and offers physical insights into the electronic structure properties of transcription factor complexes and DNA motifs. The tight binding Hamiltonian parameters are generated using the random forest regression algorithm, which reproduces the given ab-initio level calculations with reasonable accuracy. We present a library of residue-level parameters derived from extensive electronic structure calculations over various possible combinations of nucleobases and amino acid side chains from high-quality DNA-protein complex structures. As an example, our approach can reasonably generate the subtle electronic structure details for the orthologous transcription factors human AP-1 and Epstein-Barr virus Zta within a few seconds on a laptop. This method potentially enhances our understanding of the electronic structure variations of gene-protein interaction complexes, even those involving dozens of proteins and genes. We hope this study offers a powerful tool for analyzing transcription regulation mechanisms at an electronic structural level.

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Machine Learning and Deep Learning

Cited by 2 publications

References 61 publications

Energy-efficient design for green indoor OWC-IoT systems using passive reflective filters and machine learning-assisted quality prediction

Energy-efficient design for green indoor OWC-IoT systems using passive reflective filters and machine learning-assisted quality prediction

Elucidating Electronic Structure Variations in Nucleic Acid-Protein Complexes Involved in Transcription Regulation Using a Tight-Binding Approach

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