04415nam 2200937z- 450 991056646540332120231214133329.0(CKB)5680000000037726(oapen)https://directory.doabooks.org/handle/20.500.12854/81117(EXLCZ)99568000000003772620202205d2022 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierRecent Trends in Computational Research on DiseasesBaselMDPI - Multidisciplinary Digital Publishing Institute20221 electronic resource (130 p.)3-0365-3230-7 3-0365-3231-5 Recent advances in information technology have brought forth a paradigm shift in science, especially in the biology and medical fields. Statistical methodologies based on high-performance computing and big data analysis are now indispensable for the qualitative and quantitative understanding of experimental results. In fact, the last few decades have witnessed drastic improvements in high-throughput experiments in health science, for example, mass spectrometry, DNA microarray, next generation sequencing, etc. Those methods have been providing massive data involving four major branches of omics (genomics, transcriptomics, proteomics, and metabolomics). Information about amino acid sequences, protein structures, and molecular structures are fundamental data for the prediction of bioactivity of chemical compounds when screening drugs. On the other hand, cell imaging, clinical imaging, and personal healthcare devices are also providing important data concerning the human body and disease. In parallel, various methods of mathematical modelling such as machine learning have developed rapidly. All of these types of data can be utilized in computational approaches to understand disease mechanisms, diagnosis, prognosis, drug discovery, drug repositioning, disease biomarkers, driver mutations, copy number variations, disease pathways, and much more. In this Special Issue, we have published 8 excellent papers dedicated to a variety of computational problems in the biomedical field from the genomic level to the whole-person physiological level.Technology: general issuesbicsscHistory of engineering & technologybicsscwater temperaturebathingECGheart rate variabilityquantitative analysist-testhypertrophic cardiomyopathydata miningautomated curationmolecular mechanismsatrial fibrillationsudden cardiac deathheart failureleft ventricular outflow tract obstructioncardiac fibrosismyocardial ischemiacompound-protein interactionJamumachine learningdrug discoveryherbal medicinedata augmentationdeep learningECG quality assessmentdrug-target interactionsprotein-protein interactionschronic diseasesdrug repurposingmaximum flowadenosine methylationm6ARNA modificationneuronal developmentgenetic variationcopy number variantsdisease-related traitssequential orderassociation testblood pressurecuffless measurementlongitudinal experimentplethysmographnonlinear regressionTechnology: general issuesHistory of engineering & technologyAltaf-Ul-Amin Mdedt1328529Kanaya ShigehikoedtOno NaoakiedtHuang MingedtAltaf-Ul-Amin MdothKanaya ShigehikoothOno NaoakiothHuang MingothBOOK9910566465403321Recent Trends in Computational Research on Diseases3038651UNINA