<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-05-27T05:32:34Z</responseDate><request verb="GetRecord" identifier="oai:riuma.uma.es:10630/35328" metadataPrefix="mods">https://riuma.uma.es/rest/oai/request</request><GetRecord><record><header><identifier>oai:riuma.uma.es:10630/35328</identifier><datestamp>2026-02-03T10:58:50Z</datestamp><setSpec>com_10630_2254</setSpec><setSpec>col_10630_37953</setSpec></header><metadata><mods:mods xmlns:doc="http://www.lyncode.com/xoai" xmlns:mods="http://www.loc.gov/mods/v3" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-1.xsd">
   <mods:name>
      <mods:namePart>Carbonell-Ballesteros, Max</mods:namePart>
   </mods:name>
   <mods:name>
      <mods:namePart>Durán-Nebreda, Salva</mods:namePart>
   </mods:name>
   <mods:name>
      <mods:namePart>Montañez, Raúl</mods:namePart>
   </mods:name>
   <mods:name>
      <mods:namePart>Macía, Javier</mods:namePart>
   </mods:name>
   <mods:name>
      <mods:namePart>Rodríguez-Caso, Carlos Francisco</mods:namePart>
   </mods:name>
   <mods:extension>
      <mods:dateAvailable encoding="iso8601">2024-11-26T12:30:07Z</mods:dateAvailable>
   </mods:extension>
   <mods:extension>
      <mods:dateAccessioned encoding="iso8601">2024-11-26T12:30:07Z</mods:dateAccessioned>
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   <mods:originInfo>
      <mods:dateIssued encoding="iso8601">2014-12-16</mods:dateIssued>
   </mods:originInfo>
   <mods:identifier type="citation">Max Carbonell-Ballestero, Salva Duran-Nebreda, Raúl Montañez, Ricard Solé, Javier Macía, Carlos Rodríguez-Caso, A bottom-up characterization of transfer functions for synthetic biology designs: lessons from enzymology, Nucleic Acids Research, Volume 42, Issue 22, 16 December 2014, Pages 14060–14069, https://doi.org/10.1093/nar/gku964</mods:identifier>
   <mods:identifier type="uri">https://hdl.handle.net/10630/35328</mods:identifier>
   <mods:identifier type="doi">10.1093/nar/gku964</mods:identifier>
   <mods:abstract>Within the field of synthetic biology, a rational design of genetic parts should include a causal understanding of their input-output responses-the so-called transfer function-and how to tune them. However, a commonly adopted strategy is to fit data to Hill-shaped curves without considering the underlying molecular mechanisms. Here we provide a novel mathematical formalization that allows prediction of the global behavior of a synthetic device by considering the actual information from the involved biological parts. This is achieved by adopting an enzymology-like framework, where transfer functions are described in terms of their input affinity constant and maximal response. As a proof of concept, we characterize a set of Lux homoserine-lactone-inducible genetic devices with different levels of Lux receptor and signal molecule. Our model fits the experimental results and predicts the impact of the receptor's ribosome-binding site strength, as a tunable parameter that affects gene expression. The evolutionary implications are outlined.</mods:abstract>
   <mods:language>
      <mods:languageTerm>eng</mods:languageTerm>
   </mods:language>
   <mods:accessCondition type="useAndReproduction">open access</mods:accessCondition>
   <mods:subject>
      <mods:topic>Enzimología</mods:topic>
   </mods:subject>
   <mods:titleInfo>
      <mods:title>A bottom-up characterization of transfer functions for synthetic biology designs: lessons from enzymology</mods:title>
   </mods:titleInfo>
   <mods:genre>journal article</mods:genre>
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