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Bio-AIMS collection of chemoinformatics web tools based on molecular graph information and artificial intelligence models
(Bentham, 2015-09-01)
[Abstract] The molecular information encoding into molecular descriptors is the first step into in silico Chemoinformatics methods in Drug Design. The Machine Learning methods are a complex solution to find prediction ...
ANN multiscale model of anti-HIV Drugs activity vs AIDS prevalence in the US at county level based on information indices of molecular graphs and social networks
(American Chemical Society, 2014)
[Abstract] This work is aimed at describing the workflow for a methodology that combines chemoinformatics and pharmacoepidemiology methods and at reporting the first predictive model developed with this methodology. The ...
Carbon nanotubes’ effect on mitochondrial oxygen flux dynamics: polarography experimental study and machine learning models using star graph trace invariants of Raman spectra
(MDPI, 2017-11-11)
[Abstract] This study presents the impact of carbon nanotubes (CNTs) on mitochondrial oxygen mass flux (Jm) under three experimental conditions. New experimental results and a new methodology are reported for the first ...
Decrypting strong and weak single-walled carbon nanotubes interactions with mitochondrial voltage-dependent anion channels using molecular docking and perturbation theory
(Nature, 2017-10-16)
[Abstract] The current molecular docking study provided the Free Energy of Binding (FEB) for the interaction (nanotoxicity) between VDAC mitochondrial channels of three species (VDAC1-Mus musculus, VDAC1-Homo sapiens, ...
Net-net Auto machine learning (AutoML) prediction of complex ecosystems
(Nature, 2018-08-17)
[Abstract] Biological Ecosystem Networks (BENs) are webs of biological species (nodes) establishing trophic relationships (links). Experimental confirmation of all possible links is difficult and generates a huge volume ...
Experimental and computational studies of fatty acid distribution networks
(Royal Society of Chemistry, 2015-08-06)
[Abstract] Unbalanced uptake of Omega 6/Omega 3 (ω-6/ω-3) ratios could increase chronic disease occurrences, such as inflammation, atherosclerosis, or tumor proliferation, and methylation methods for measuring the ruminal ...
Experimental study and random forest prediction model of microbiome cell surface hydrophobicity
(Elsevier, 2016-11-09)
[Abstract] The cell surface hydrophobicity (CSH) is an assessable physicochemical property used to evaluate the microbial adhesion to the surface of biomaterials, which is an essential step in the microbial biofilm formation ...
Gene prioritization, communality analysis, networking and metabolic integrated pathway to better understand breast cancer pathogenesis
(Nature, 2018-11-12)
[Abstract] Consensus strategy was proved to be highly efficient in the recognition of gene-disease association. Therefore, the main objective of this study was to apply theoretical approaches to explore genes and communities ...
Perturbation theory/machine learning model of ChEMBL data for dopamine targets: docking, synthesis, and assay of new l-prolyl-l-leucyl-glycinamide peptidomimetics
(American Chemical Society, 2018-05-23)
[Abstract] Predicting drug–protein interactions (DPIs) for target proteins involved in dopamine pathways is a very important goal in medicinal chemistry. We can tackle this problem using Molecular Docking or Machine Learning ...
