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Detalle de: Sensbio: an online server for biosensor design

Title Sensbio: an online server for biosensor design
Abstract

Allosteric transcription factor (aTF) based biosensors can be used to engineer genetic circuits for a wide range of applications. The literature and online databases contain hundreds of experimentally validated molecule-TF pairs; however, the knowledge is scattered and often incomplete. Additionally, compared to the number of compounds that can be produced in living systems, those with known associated TF-compound interactions are low. For these reasons, new tools that help researchers find new possible TF-ligand pairs are called for. In this work, we present Sensbio, a computational tool that through similarity comparison against a TF-ligand reference database, is able to identify putative transcription factors that can be activated by a given input molecule. In addition to the collection of algorithms, an online application has also been developed, together with a predictive model created to find new possible matches based on machine learning.

Apa Reference Tellechea-Luzardo, J., Martín Lázaro, H., Moreno López, R. & Carbonell, P. (2023). Sensbio: an online server for biosensor design. BMC Bioinformatics, 24(1). 10.1186/s12859-023-05201-7
Doi 10.1186/s12859-023-05201-7
Publication Date 28 Feb 2023
Publication Type Software
Researcher Pablo Carbonell
Ontology Artificial Intelligence, Machine Learning in Biology, Molecular flexibility, Biological Databases, Regulatory biology, Molecular Interactions/Docking, Synthetic biology
Research Groups
Tools Sensbio

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