Molecular Computing and Bioinformatics

doi:10.3390/books978-3-03921-196-8

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Keywords

prostate cancer; Mycoplasma hominis; endoplasmic reticulum; systems biology; protein targeting; biomedical text mining; big data; Tianhe-2; parallel computing; load balancing; bacterial computing; bacteria and plasmid system; Turing universality; recursively enumerable function; miRNA biogenesis; structural patterns; DCL1; protein–protein interaction (PPI); clustering; protein complex; penalized matrix decomposition; avian influenza virus; interspecies transmission; amino acid mutation; machine learning; Bayesian causal model; causal direction learning; K2; brain storm optimization; line graph; Cartesian product graph; join graph; atom-bond connectivity index; geometric arithmetic index; P-glycoprotein; efflux ratio; in silico; machine learning; hierarchical support vector regression; absorption; distribution; metabolism; excretion; toxicity; image encryption; chaotic map; DNA coding; Hamming distance; Stenotrophomonas maltophilia; iron acquisition systems; iron-depleted; RAST server; NanoString Technologies; siderophores; gene fusion data; gene susceptibility prioritization; evaluating driver partner; gene networks; drug-target interaction prediction; machine learning; drug discovery; microRNA; environmental factor; structure information; similarity network; bioinformatics; identification of Chinese herbal medicines; biochip technology; DNA barcoding technology; DNA strand displacement; cascade; 8-bit adder/subtractor; domain label; Alzheimer’s disease; gene coding protein; sequence information; support vector machine; classification; adverse drug reaction prediction; heterogeneous information network embedding; stacking denoising auto-encoder; meta-path-based proximity; Panax ginseng; oligopeptide transporter; flowering plant; phylogeny; transcription factor; multiple interaction networks; function prediction; multinetwork integration; low-dimensional representation; dihydrouridine; nucleotide physicochemical property; pseudo dinucleotide composition; RNA secondary structure; ensemble classifier; diabetes mellitus; hypoxia-inducible factor-1α; angiogenesis; bone formation; osteogenesis; protein transduction domain; membrane computing; edge detection; enzymatic numerical P system; resolution free; molecular computing; molecular learning; DNA computing; self-organizing systems; pattern classification; machine learning; laccase; Brassica napus; lignification; stress; molecular computing; bioinformatics; machine learning; protein; DNA; RNA; drug; bio-inspired

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Molecular Computing and Bioinformatics

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July 2019

390 pages

ISBN978-3-03921-195-1 (Paperback)
ISBN978-3-03921-196-8 (PDF)

https://doi.org/10.3390/books978-3-03921-196-8

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This is a Reprint of the Special Issue Molecular Computing and Bioinformatics that was published in

Chemistry & Materials Science

Medicine & Pharmacology

Summary

This text will provide the most recent knowledge and advances in the area of molecular computing and bioinformatics. Molecular computing and bioinformatics have a close relationship, paying attention to the same object but working towards different orientations. The articles will range from topics such as DNA computing and membrane computing to specific biomedical applications, including drug R&D and disease analysis.

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