AIMC Topic: Systems Biology

Clear Filters Showing 101 to 110 of 142 articles

A tree-like Bayesian structure learning algorithm for small-sample datasets from complex biological model systems.

BMC systems biology
BACKGROUND: There are increasing efforts to bring high-throughput systems biology techniques to bear on complex animal model systems, often with a goal of learning about underlying regulatory network structures (e.g., gene regulatory networks). Howev...

Proto-object categorisation and local gist vision using low-level spatial features.

Bio Systems
Object categorisation is a research area with significant challenges, especially in conditions with bad lighting, occlusions, different poses and similar objects. This makes systems that rely on precise information unable to perform efficiently, like...

A tuberculosis ontology for host systems biology.

Tuberculosis (Edinburgh, Scotland)
A major hurdle facing tuberculosis (TB) investigators who want to utilize a rapidly growing body of data from both systems biology approaches and omics technologies is the lack of a standard vocabulary for data annotation and reporting. Lacking a mea...

Combining computational models, semantic annotations and simulation experiments in a graph database.

Database : the journal of biological databases and curation
Model repositories such as the BioModels Database, the CellML Model Repository or JWS Online are frequently accessed to retrieve computational models of biological systems. However, their storage concepts support only restricted types of queries and ...

Knowledge bases, clinical decision support systems, and rapid learning in oncology.

Journal of oncology practice
One of the most important benefits of health information technology is to assist the cognitive process of the human mind in the face of vast amounts of health data, limited time for decision making, and the complexity of the patient with cancer. Clin...

Inter-species pathway perturbation prediction via data-driven detection of functional homology.

Bioinformatics (Oxford, England)
MOTIVATION: Experiments in animal models are often conducted to infer how humans will respond to stimuli by assuming that the same biological pathways will be affected in both organisms. The limitations of this assumption were tested in the IMPROVER ...

Speaking Mathematical Models into Existence.

Cancer research
Mathematical and computational modeling enables in silico testing of hypotheses, experimental design, and interventional strategies. However, building, sharing, and applying complex models require technical skills and software development knowledge t...

A Roadmap for the Future of Systems Biology in Cancer Research.

Cancer research
Cancer systems biology seeks to understand how cancer arises as a system of interconnected molecules, cells, and tissues, with the goal of understanding, predicting, and controlling the disease. In the last decade, the field has rapidly grown as adva...

Artificial intelligence and systems biology analysis in stem cell research and therapeutics development.

Stem cells translational medicine
BACKGROUND: Stem cell research has rapidly advanced during the past decades, but the translation into approved clinical products is still lagging behind. Multiple barriers to effective clinical translation exist. We hypothesize that an ineffective us...

The dawn of a new era: can machine learning and large language models reshape QSP modeling?

Journal of pharmacokinetics and pharmacodynamics
Quantitative Systems Pharmacology (QSP) has emerged as a cornerstone of modern drug development, providing a robust framework to integrate data from preclinical and clinical studies, enhance decision-making, and optimize therapeutic strategies. By mo...