Learning of signaling networks: molecular mechanisms
P Csermely, N Kunsic, P Mendik, M Kerestély… - Trends in biochemical …, 2020 - cell.com
Molecular processes of neuronal learning have been well described. However, learning
mechanisms of non-neuronal cells are not yet fully understood at the molecular level. Here …
mechanisms of non-neuronal cells are not yet fully understood at the molecular level. Here …
CODA: Integrating multi-level context-oriented directed associations for analysis of drug effects
In silico network-based methods have shown promising results in the field of drug
development. Yet, most of networks used in the previous research have not included context …
development. Yet, most of networks used in the previous research have not included context …
Hmrbase2: a comprehensive database of hormones and their receptors
Purpose Hormones play a critical role in regulating various physiological processes and any
hormonal imbalances can lead to major endocrine disorders. Thus, studying hormones is …
hormonal imbalances can lead to major endocrine disorders. Thus, studying hormones is …
HormoNet: a deep learning approach for hormone-drug interaction prediction
N Emami, R Ferdousi - BMC bioinformatics, 2024 - Springer
Several experimental evidences have shown that the human endogenous hormones can
interact with drugs in many ways and affect drug efficacy. The hormone drug interactions …
interact with drugs in many ways and affect drug efficacy. The hormone drug interactions …
Predicting cross-tissue hormone–gene relations using balanced word embeddings
A Jadhav, T Kumar, M Raghavendra… - …, 2022 - academic.oup.com
Motivation Inter-organ/inter-tissue communication is central to multi-cellular organisms
including humans, and mapping inter-tissue interactions can advance system-level whole …
including humans, and mapping inter-tissue interactions can advance system-level whole …
Predicting herb-disease associations using network-based measures in human protein interactome
Background Natural herbs are frequently used to treat diseases or to relieve symptoms in
many countries. Moreover, as their safety has been proven for a long time, they are …
many countries. Moreover, as their safety has been proven for a long time, they are …
HIDEEP: a systems approach to predict hormone impacts on drug efficacy based on effect paths
Experimental evidence has shown that some of the human endogenous hormones
significantly affect drug efficacy. Since hormone status varies with individual physiological …
significantly affect drug efficacy. Since hormone status varies with individual physiological …
CODA-ML: context-specific biological knowledge representation for systemic physiology analysis
Background Computational analysis of complex diseases involving multiple organs requires
the integration of multiple different models into a unified model. Different models are often …
the integration of multiple different models into a unified model. Different models are often …
[PDF][PDF] Knowledge Integration and Representation for Biomedical Analysis
H Alachram - 2021 - ediss.uni-goettingen.de
Abstract Information-based health systems aimed at improving clinical decision-making are
appealing as they are able to cope with the rising amount of information that clinicians are …
appealing as they are able to cope with the rising amount of information that clinicians are …
Compilation and mining of peptide hormones and their receptors
D Kaur, GPS Raghava - 2022 - repository.iiitd.edu.in
Hormones play a crucial role in communicating information between cells and organs;
responsible for regulating almost all the physiological processes of organisms. Thus, it is …
responsible for regulating almost all the physiological processes of organisms. Thus, it is …