A review of causal discovery methods for molecular network analysis

J Kelly, C Berzuini, B Keavney… - Molecular genetics & …, 2022 - Wiley Online Library
Background With the increasing availability and size of multi‐omics datasets, investigating
the casual relationships between molecular phenotypes has become an important aspect of …

Connecting the Dots: Using Machine Learning to Forge Gene Regulatory Networks from Large Biological Datasets. At the Intersection of GRNs: Where System Biology …

I Monga, V Randhawa, SK Dhanda - Machine Learning and Systems …, 2022 - Springer
The last decade witnessed the exponential increase in the large and complex biological
datasets. These studies range from human to different species under different conditions like …

Integrated regulatory and metabolic networks of the tumor microenvironment for therapeutic target prioritization

T Shi, H Yu, RH Blair - Statistical Applications in Genetics and …, 2023 - degruyter.com
Translation of genomic discovery, such as single-cell sequencing data, to clinical decisions
remains a longstanding bottleneck in the field. Meanwhile, computational systems biological …

Discovery methods for systematic analysis of causal molecular networks in modern omics datasets

J Kelly, C Berzuini, B Keavney, M Tomaszewski… - arXiv preprint arXiv …, 2022 - arxiv.org
With the increasing availability and size of multi-omics datasets, investigating the casual
relationships between molecular phenotypes has become an important aspect of exploring …

Identification of Candidate Biomarkers and Potential Therapeutics for Idiopathic Pulmonary Fibrosis Through Systems Biology Approaches

MN Akça - 2023 - search.proquest.com
İdiyopatik pulmoner fibrozis (İPF), etiyolojisi bilinmeyen, akciğer skarlaşması, aşırı hücre dışı
matriks birikimi, akciğer fonksiyon kaybı ile karakterize edilen kronik ve ilerleyici bir …

Optimizing feature selection parameters using statistically equivalent signature (SES) algorithm

UM Khaire, R Dhanalakshmi - 2019 4th International …, 2019 - ieeexplore.ieee.org
Selection of important feature from the high dimensional dataset is a very important task.
Irrelevant and insignificant features can hinder the important information of the dataset. For …