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Systems Biology

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Assessing the Anti-cancer Therapeutic Mechanism of a Herbal Combination for Breast Cancer on System-level by a Network Pharmacological Approach.

Anticancer research
BACKGROUND/AIM: Accumulating evidence has shown therapeutic effects of herbals on breast cancer, a commonly diagnosed malignancy in women worldwide. However, their underlying mechanisms remain unclear. We aimed to explore the mode of action of a rece...

Multi-omics integration-a comparison of unsupervised clustering methodologies.

Briefings in bioinformatics
With the recent developments in the field of multi-omics integration, the interest in factors such as data preprocessing, choice of the integration method and the number of different omics considered had increased. In this work, the impact of these f...

Dissecting celastrol with machine learning to unveil dark pharmacology.

Chemical communications (Cambridge, England)
By coalescing bespoke machine learning and bioinformatics analyses with cell-based assays, we unveil the pharmacology of celastrol. Celastrol is a direct modulator of the progesterone and cannabinoid receptors, and its effects correlate with the anti...

A Systems Toxicology Approach for the Prediction of Kidney Toxicity and Its Mechanisms In Vitro.

Toxicological sciences : an official journal of the Society of Toxicology
The failure to predict kidney toxicity of new chemical entities early in the development process before they reach humans remains a critical issue. Here, we used primary human kidney cells and applied a systems biology approach that combines multidim...

Unsupervised GRN Ensemble.

Methods in molecular biology (Clifton, N.J.)
Inferring gene regulatory networks from expression data is a very challenging problem that has raised the interest of the scientific community. Different algorithms have been proposed to try to solve this issue, but it has been shown that different m...

Tree-Based Learning of Regulatory Network Topologies and Dynamics with Jump3.

Methods in molecular biology (Clifton, N.J.)
Inference of gene regulatory networks (GRNs) from time series data is a well-established field in computational systems biology. Most approaches can be broadly divided in two families: model-based and model-free methods. These two families are highly...

A review on machine learning principles for multi-view biological data integration.

Briefings in bioinformatics
Driven by high-throughput sequencing techniques, modern genomic and clinical studies are in a strong need of integrative machine learning models for better use of vast volumes of heterogeneous information in the deep understanding of biological syste...

A heuristic method for simulating open-data of arbitrary complexity that can be used to compare and evaluate machine learning methods.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
A central challenge of developing and evaluating artificial intelligence and machine learning methods for regression and classification is access to data that illuminates the strengths and weaknesses of different methods. Open data plays an important...