ArticleScience signaling2011
Introduction to network analysis in systems biology.
Article in Science signaling, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
54 citing papers in PubMed.
- PMconv: How to Compare Proteomes and Metabolomes?International journal of molecular sciences · 2026Article
- A novel explainable deep-learning approach for network analysis of epistatic interactions.NAR genomics and bioinformatics · 2026Article
- Article
- Shared Genetic Characteristics of Coronary Artery Disease and Peripheral artery Disease: Insights From Integrated Bioinformatics Analysis of RNA-Sequencing Data.Bioinformatics and biology insights · 2025Article
- MiRNA target enrichment analysis of co-expression network modules reveals important miRNAs and their roles in breast cancer progression.Journal of integrative bioinformatics · 2024Article
- A primer for quantum computing and its applications to healthcare and biomedical research.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Mycobiome analysis of leaf, root, and soil of symptomatic oil palm trees (Frontiers in microbiology · 2024Article
- Exploring Co-occurrence patterns and microbial diversity in the lung microbiome of patients with non-small cell lung cancer.BMC microbiology · 2023Article
- Signed Distance Correlation (SiDCo): an online implementation of distance correlation and partial distance correlation for data-driven network analysis.Bioinformatics (Oxford, England) · 2023Article
- Impaired Awareness in People with Severe Alcohol-Related Cognitive Deficits Including Korskoff's Syndrome: A Network Analysis.Journal of clinical medicine · 2023Article
- Is Cancer Reversible? Rethinking Carcinogenesis Models-A New Epistemological Tool.Biomolecules · 2023Review
- Unravelling microalgal-bacterial interactions in aquatic ecosystems through 16S rRNA gene-based co-occurrence networks.Scientific reports · 2023Article
- Editorial: Expert Opinions in Network bioinformatics: 2022.Frontiers in bioinformatics · 2023Article
- Functional selectivity of Receptor Tyrosine Kinases regulates distinct cellular outputs.Frontiers in cell and developmental biology · 2023Review
- Integration of multi-omics data to elucidate keystone unknown taxa within microbialite-forming ecosystems.Frontiers in microbiology · 2023Article
- Response of the soil microbial community to petroleum hydrocarbon stress shows a threshold effect: research on aged realistic contaminated fields.Frontiers in microbiology · 2023Article
- Applications of Boolean modeling to study the dynamics of a complex disease and therapeutics responses.Frontiers in bioinformatics · 2023Article
- A practical two-sample test for weighted random graphs.Journal of applied statistics · 2023Article
- NESM: a network embedding method for tumor stratification by integrating multi-omics data.G3 (Bethesda, Md.) · 2022Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
This Teaching Resource provides lecture notes, slides, and a problem set for a set of three lectures from a course entitled "Systems Biology: Biomedical Modeling." The materials are from three separate lectures introducing applications of graph theory and network analysis in systems biology. The first lecture describes different types of intracellular networks, methods for constructing biological networks, and different types of graphs used to represent regulatory intracellular networks. The second lecture surveys milestones and key concepts in network analysis by introducing topological measures, random networks, growing network models, and topological observations from molecular biological systems abstracted to networks. The third lecture discusses methods for analyzing lists of genes and experimental data in the context of prior knowledge networks to make predictions.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.