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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Handbook of Machine Learning Applications for Genomics

Handbook of Machine Learning Applications for Genomics

Roy, Sanjiban Sekhar
Taguchi, Y. -H

Hardcover

Series: Studies in Big Data, Book 103

Technology & EngineeringGeneral ComputersGenetics

ISBN10: 9811691576
ISBN13: 9789811691577
Publisher: Springer Nature
Published: Jun 24 2022
Pages: 218
Weight: 1.10
Height: 0.56 Width: 6.14 Depth: 9.21
Language: English
Local and global characterization of genomic data.- DNA sequencing using RNN.- Deep learning to study functional activities of DNA sequence.- Autoencoders for gene clastering.- Dimension reduction in gene expression using deep learning.- To predict DNA methylation states using deep learning.- Transfer learning in genomics.- CNN model to analyze gene expression images.- Gene expression Prediction using advanced machine learning.- Predicting splicing regulation using deep learning.- Transcription factor binding site prediction using deep learning.- Deep learning for prediction of structural classification of proteins.- Prediction of secondary strucure of RNA using advanced machine learning and deep learning.- Deep learning for pepositioning of drug and pharmacogenomics.

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