Gene regulatory networks and their applications: understanding biological and medical problems in terms of networks
F Emmert-Streib, M Dehmer… - Frontiers in cell and …, 2014 - frontiersin.org
In recent years gene regulatory networks (GRNs) have attracted a lot of interest and many
methods have been introduced for their statistical inference from gene expression data …
methods have been introduced for their statistical inference from gene expression data …
Understanding statistical hypothesis testing: The logic of statistical inference
F Emmert-Streib, M Dehmer - Machine Learning and Knowledge …, 2019 - mdpi.com
Statistical hypothesis testing is among the most misunderstood quantitative analysis
methods from data science. Despite its seeming simplicity, it has complex …
methods from data science. Despite its seeming simplicity, it has complex …
Characteristics of blood–brain barrier heterogeneity between brain regions revealed by profiling vascular and perivascular cells
The blood–brain barrier (BBB) protects the brain and maintains neuronal homeostasis. BBB
properties can vary between brain regions to support regional functions, yet how BBB …
properties can vary between brain regions to support regional functions, yet how BBB …
ATTED-II v11: a plant gene coexpression database using a sample balancing technique by subagging of principal components
T Obayashi, H Hibara, Y Kagaya, Y Aoki… - Plant and Cell …, 2022 - academic.oup.com
Abstract ATTED-II (https://atted. jp) is a gene coexpression database for nine plant species
based on publicly available RNAseq and microarray data. One of the challenges in …
based on publicly available RNAseq and microarray data. One of the challenges in …
Network inference in systems biology: recent developments, challenges, and applications
MM Saint-Antoine, A Singh - Current opinion in biotechnology, 2020 - Elsevier
One of the most interesting, difficult, and potentially useful topics in computational biology is
the inference of gene regulatory networks (GRNs) from expression data. Although …
the inference of gene regulatory networks (GRNs) from expression data. Although …
BTR: training asynchronous Boolean models using single-cell expression data
Background Rapid technological innovation for the generation of single-cell genomics data
presents new challenges and opportunities for bioinformatics analysis. One such area lies in …
presents new challenges and opportunities for bioinformatics analysis. One such area lies in …
Toxicogenomics Data for Chemical Safety Assessment and Development of New Approach Methodologies: An Adverse Outcome Pathway‐Based Approach
Mechanistic toxicology provides a powerful approach to inform on the safety of chemicals
and the development of safe‐by‐design compounds. Although toxicogenomics supports …
and the development of safe‐by‐design compounds. Although toxicogenomics supports …
Autoregressive models for gene regulatory network inference: Sparsity, stability and causality issues
G Michailidis, F d'Alché-Buc - Mathematical biosciences, 2013 - Elsevier
Reconstructing gene regulatory networks from high-throughput measurements represents a
key problem in functional genomics. It also represents a canonical learning problem and …
key problem in functional genomics. It also represents a canonical learning problem and …
Reverse engineering of genome-wide gene regulatory networks from gene expression data
ZP Liu - Current genomics, 2015 - ingentaconnect.com
Transcriptional regulation plays vital roles in many fundamental biological processes.
Reverse engineering of genome-wide regulatory networks from high-throughput …
Reverse engineering of genome-wide regulatory networks from high-throughput …
A network toxicology approach for mechanistic modelling of nanomaterial hazard and adverse outcomes
Hazard assessment is the first step in evaluating the potential adverse effects of chemicals.
Traditionally, toxicological assessment has focused on the exposure, overlooking the impact …
Traditionally, toxicological assessment has focused on the exposure, overlooking the impact …