ReviewMethods in molecular biology (Clifton, N.J.)2025
Review on Advancement of AI in Cell Engineering and Molecular Biology.
Review in Methods in molecular biology (Clifton, N.J.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence is emerging as an important domain in the scientific field with the potential to provide advancements in molecular biology and cell engineering to improve the quality of life of human beings. The convergence of AI and related technologies linked with biology can lower the technical and knowledge barriers in numerous areas, such as diagnostics and forecasting. Artificial intelligence (AI) and machine learning tools are revolutionizing life science research and biomedical applications. Examples include understanding ecosystems across space and time, designing new drugs, deciphering molecular data and biomedical images, and predicting the 3D structures of proteins. Cellular engineering is a new field that has arisen as biomedical engineering has moved from the organ and tissue level to the cellular and subcellular level. Through the automated and programmatically enabled finding of tissue-level patterns and design principles, AI presents a radically new paradigm for tissue engineering research.Molecular biology delves into the intricate mechanisms governing life at its most fundamental level-the molecular scale, exploring the structure, function, and interactions of biological molecules such as DNA, RNA, proteins, and lipids. AI has spearheaded remarkable advancements in molecular biology, fundamentally transforming numerous facets of research, including drug discovery, protein structure prediction, genomic analysis, drug repurposing, synthetic biology, and disease diagnosis and prognosis. Moreover, this chapter demonstrates the fundamental potentials of AI and their applications focusing on molecular biology and cellular engineering.
Indexed as
Identifiers
40553333What 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.