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 …

CODA: Integrating multi-level context-oriented directed associations for analysis of drug effects

H Yu, J Jung, S Yoon, M Kwon, S Bae, S Yim, J Lee… - Scientific reports, 2017 - nature.com
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 …

Hmrbase2: a comprehensive database of hormones and their receptors

D Kaur, A Arora, S Patiyal, GPS Raghava - Hormones, 2023 - Springer
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 …

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 …

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 …

Predicting herb-disease associations using network-based measures in human protein interactome

S Wang, HC Lee, S Lee - BMC Complementary Medicine and Therapies, 2024 - Springer
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 …

HIDEEP: a systems approach to predict hormone impacts on drug efficacy based on effect paths

M Kwon, J Jung, H Yu, D Lee - Scientific Reports, 2017 - nature.com
Experimental evidence has shown that some of the human endogenous hormones
significantly affect drug efficacy. Since hormone status varies with individual physiological …

CODA-ML: context-specific biological knowledge representation for systemic physiology analysis

M Kwon, S Yim, G Kim, S Lee, C Jeong, D Lee - BMC bioinformatics, 2019 - Springer
Background Computational analysis of complex diseases involving multiple organs requires
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 …

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 …