Molecular Computing and Bioinformatics

© 2019 by the authors; CC BY-NC-ND license

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