NutriFD: Proving the medicinal value of food nutrition based on food-disease association and treatment networks [PDF]
arXiv, 2023 There is rising evidence of the health benefit associated with specific dietary interventions. Current food-disease databases focus on associations and treatment relationships but haven't provided a reasonable assessment of the strength of the relationship, and lack of attention on food nutrition.
arxiv
Quantum Kolmogorov Complexity and Information-Disturbance Theorem [PDF]
Entropy 13, 778-789 (2011), 2011 In this paper, a representation of the information-disturbance theorem based on the quantum Kolmogorov complexity that was defined by P. Vitanyi has been examined. In the quantum information theory, the information-disturbance relationship, which treats the trade-off relationship between information gain and its caused disturbance, is a fundamental ...
arxiv +1 more source
Quantitative Structure-Activity Relationship Analysis of the Anticonvulsant Activity of Some Benzylacetamides Based on Genetic Algorithm-Based Multiple Linear Regression [PDF]
, 2011 Purpose: To develop the quantitative structure-activity relationship (QSAR) for predicting the anticonvulsant activity of α-substituted acetamido-N-benzylacetamide derivatives.Methods: AM1 semiempirical quantum chemical calculation method was used
Ardakani, SS, Marjani, M, Najafi, A
core +2 more sources
Recurrence and algorithmic information [PDF]
, 2003 In this paper we initiate a somewhat detailed investigation of the relationships between quantitative recurrence indicators and algorithmic complexity of orbits in weakly chaotic dynamical systems. We mainly focus on examples.
arxiv +1 more source
Node-based Knowledge Graph Contrastive Learning for Medical Relationship Prediction [PDF]
arXiv, 2023 The embedding of Biomedical Knowledge Graphs (BKGs) generates robust representations, valuable for a variety of artificial intelligence applications, including predicting drug combinations and reasoning disease-drug relationships. Meanwhile, contrastive learning (CL) is widely employed to enhance the distinctiveness of these representations.
arxiv
In vitro antiplasmodial activity of1,1 0-phenanthroline derivatives and its quantitative structure-activity relationship [PDF]
, 2003 Mustofa, Ange Desire Yapi, Alexis Valentin, lqmal Tahir - In vitro antiplasmodial activity of 1,10- phenanthroline derivatives and its quantitative structure-activity relationship Background: Previous study showed that 1,10-phenanthroline skeleton were ...
Mustofa, Ange Desire Yapi, Alexis Valentin, lqmal Tahir
core +1 more source
Quantitative Structure-Activity Relationship Modeling and Bayesian Networks: Optimality of Naive Bayes Model [PDF]
, 2019 Previously, computational drag design was usually based on simplified laws of molecular physics, used for calculation of ligand’s interaction with an active site of a protein-enzyme.
Kupervasser, Oleg
core +1 more source
Quantitative structure-activity relationship models with receptor-dependent descriptors for predicting peroxisome proliferator-activated receptor activities of thiazolidinedione and oxazolidinedione derivatives [PDF]
, 2009 A quantitative structure–activity relationship study has been carried out, in which the relationship between the peroxisome proliferator-activated receptor a and the peroxisome proliferator activated receptor c agonistic activities of thiazo ...
Fernandes, Miguel X. +2 more
core +1 more source
Malaria Journal, 2021 Background Emergence of cross-resistance to current anti-malarial drugs has led to an urgent need for identification of potential compounds with novel modes of action and anti-malarial activity against the resistant strains.
Phuong Thuy Viet Nguyen +15 more
doaj +1 more source
arXiv, 2023 Understanding how genes interact and relate to each other is a fundamental question in biology. However, current practices for describing these relationships, such as drawing diagrams or graphs in a somewhat arbitrary manner, limit our ability to integrate various aspects of the gene functions and view the genome holistically.
arxiv