Tellechea-Luzardo, J., Martin Lazaro, H., Fernandez Perez, C., Henriques, D., Otero-Muras, I., & Carbonell, P. (2025). Context-Aware Biosensor Design Through Biology-Guided Machine Learning and Dynamical Modeling. ACS Synthetic Biology, 14(6), 2094–2104. https://doi.org/10.1021/acssynbio.4c00894

Martín Lázaro, H., Marín Bautista, R., & Carbonell, P. (2024). DetSpace: a web server for engineering detectable pathways for bio-based chemical production. Nucleic Acids Research, 52(W1), W476–W480. https://doi.org/10.1093/nar/gkae287

Stoney, R. A., Hanko, E. K. R., Carbonell, P., & Breitling, R. (2023). SelenzymeRF: updated enzyme suggestion software for unbalanced biochemical reactions. Computational and Structural Biotechnology Journal, 21, 5868–5876. https://doi.org/10.1016/j.csbj.2023.11.039

Tellechea-Luzardo, J., Stiebritz, M. T., & Carbonell, P. (2023). Transcription factor-based biosensors for screening and dynamic regulation. Frontiers in Bioengineering and Biotechnology, 11. https://doi.org/10.3389/fbioe.2023.1118702

Sidorova, J., Carbonell, P., & Čukić, M. (2022). Blood Glucose Estimation From Voice: First Review of Successes and Challenges. Journal of Voice, 36(5), 737.e1-737.e10. https://doi.org/10.1016/j.jvoice.2020.08.034

Hérisson, J., Duigou, T., du Lac, M., Bazi-Kabbaj, K., Azad, M. S., Buldum, G., Telle, O., El-Moubayed, Y., Carbonell, P., Swainston, N., Zulkower, V., Kushwaha, M., Baldwin, G. S., & Faulon, J.-L. (2022). Galaxy-SynBioCAD: Automated Pipeline for Synthetic Biology Design and Engineering. https://doi.org/10.1101/2022.02.23.481618

Tellechea-Luzardo, J., Otero-Muras, I., Goñi-Moreno, A., & Carbonell, P. (2022). Fast biofoundries: coping with the challenges of biomanufacturing. Trends in Biotechnology, 40(7), 831–842. https://doi.org/10.1016/j.tibtech.2021.12.006

Tellechea-Luzardo, J., Moreno López, R., & Carbonell, P. (2022). Sensbio: An online server for biosensor design. https://doi.org/10.1101/2022.07.28.501596

Hérisson, J., Duigou, T., du Lac, M., Bazi-Kabbaj, K., Sabeti Azad, M., Buldum, G., Telle, O., El Moubayed, Y., Carbonell, P., Swainston, N., Zulkower, V., Kushwaha, M., Baldwin, G. S., & Faulon, J.-L. (2022). The automated Galaxy-SynBioCAD pipeline for synthetic biology design and engineering. Nature Communications, 13(1). https://doi.org/10.1038/s41467-022-32661-x

Otero-Muras, I., & Carbonell, P. (2021). Automated engineering of synthetic metabolic pathways for efficient biomanufacturing. Metabolic Engineering, 63, 61–80. https://doi.org/10.1016/j.ymben.2020.11.012

Yeoh, J. W., Swainston, N., Vegh, P., Zulkower, V., Carbonell, P., Holowko, M. B., Peddinti, G., & Poh, C. L. (2021). SynBiopython: an open-source software library for Synthetic Biology. Synthetic Biology, 6(1). https://doi.org/10.1093/synbio/ysab001

Robinson, C. J., Tellechea-Luzardo, J., Carbonell, P., Jervis, A. J., Yan, C., Hollywood, K. A., Dunstan, M. S., Currin, A., Takano, E., & Scrutton, N. S. (2021). Prototyping of microbial chassis for the biomanufacturing of high-value chemical targets. Biochemical Society Transactions, 49(3), 1055–1063. https://doi.org/10.1042/bst20200017

Camarena, M., & Carbonell, P. (2021). Developing an enzyme selection tool supporting multiple hosts contexts. https://doi.org/10.1101/2021.09.09.459461

Carbonell, P., Le Feuvre, R., Takano, E., & Scrutton, N. S. (2020). In silico design and automated learning to boost next-generation smart biomanufacturing. Synthetic Biology, 5(1). https://doi.org/10.1093/synbio/ysaa020

Robinson, C. J., Carbonell, P., Jervis, A. J., Yan, C., Hollywood, K. A., Dunstan, M. S., Currin, A., Swainston, N., Spiess, R., Taylor, S., Mulherin, P., Parker, S., Rowe, W., Matthews, N. E., Malone, K. J., Le Feuvre, R., Shapira, P., Barran, P., Turner, N. J., … Scrutton, N. S. (2020). Rapid prototyping of microbial production strains for the biomanufacture of potential materials monomers. Metabolic Engineering, 60, 168–182. https://doi.org/10.1016/j.ymben.2020.04.008

Boada, Y., Vignoni, A., Picó, J., & Carbonell, P. (2020). Extended Metabolic Biosensor Design for Dynamic Pathway Regulation of Cell Factories. IScience, 23(7), 101305. https://doi.org/10.1016/j.isci.2020.101305

Dunstan, M. S., Robinson, C. J., Jervis, A. J., Yan, C., Carbonell, P., Hollywood, K. A., Currin, A., Swainston, N., Feuvre, R. L., Micklefield, J., Faulon, J.-L., Breitling, R., Turner, N., Takano, E., & Scrutton, N. S. (2020). Engineering Escherichia coli towards de novo production of gatekeeper (2S)-flavanones: naringenin, pinocembrin, eriodictyol and homoeriodictyol. Synthetic Biology, 5(1). https://doi.org/10.1093/synbio/ysaa012

Kurgan, G., Kurgan, L., Schneider, A., Onyeabor, M., Rodriguez-Sanchez, Y., Taylor, E., Martinez, R., Carbonell, P., Shi, X., Gu, H., & Wang, X. (2019). Identification of major malate export systems in an engineered malate-producing Escherichia coli aided by substrate similarity search. Applied Microbiology and Biotechnology, 103(21–22), 9001–9011. https://doi.org/10.1007/s00253-019-10164-y

Currin, A., Swainston, N., Dunstan, M. S., Jervis, A. J., Mulherin, P., Robinson, C. J., Taylor, S., Carbonell, P., Hollywood, K. A., Yan, C., Takano, E., Scrutton, N. S., & Breitling, R. (2019). Highly multiplexed, fast and accurate nanopore sequencing for verification of synthetic DNA constructs and sequence libraries. Synthetic Biology, 4(1). https://doi.org/10.1093/synbio/ysz025

Jervis, A. J., Carbonell, P., Taylor, S., Sung, R., Dunstan, M. S., Robinson, C. J., Breitling, R., Takano, E., & Scrutton, N. S. (2019). SelProm: A Queryable and Predictive Expression Vector Selection Tool for Escherichia coli. ACS Synthetic Biology, 8(7), 1478–1483. https://doi.org/10.1021/acssynbio.8b00399

Carbonell, P., Radivojevic, T., & García Martín, H. (2019). Opportunities at the Intersection of Synthetic Biology, Machine Learning, and Automation. ACS Synthetic Biology, 8(7), 1474–1477. https://doi.org/10.1021/acssynbio.8b00540

Grozinger, L., Amos, M., Gorochowski, T. E., Carbonell, P., Oyarzún, D. A., Stoof, R., Fellermann, H., Zuliani, P., Tas, H., & Goñi-Moreno, A. (2019). Pathways to cellular supremacy in biocomputing. Nature Communications, 10(1). https://doi.org/10.1038/s41467-019-13232-z

Carbonell, P., Faulon, J.-L., & Breitling, R. (2019). Efficient learning in metabolic pathway designs through optimal assembling. IFAC-PapersOnLine, 52(26), 7–12. https://doi.org/10.1016/j.ifacol.2019.12.228

López-Massaguer, O., Pastor, M., Sanz, F., & Carbonell, P. (2018). Hepatotoxicity Prediction by Systems Biology Modeling of Disturbed Metabolic Pathways Using Gene Expression Data. Computational Toxicology, 505–518. https://doi.org/10.1007/978-1-4939-7899-1_23

Delépine, B., Duigou, T., Carbonell, P., & Faulon, J.-L. (2018). RetroPath2.0: A retrosynthesis workflow for metabolic engineers. Metabolic Engineering, 45, 158–170. https://doi.org/10.1016/j.ymben.2017.12.002

Carbonell, P., Wong, J., Swainston, N., Takano, E., Turner, N. J., Scrutton, N. S., Kell, D. B., Breitling, R., & Faulon, J.-L. (2018). Selenzyme: enzyme selection tool for pathway design. Bioinformatics, 34(12), 2153–2154. https://doi.org/10.1093/bioinformatics/bty065

Carbonell, P., Delépine, B., & Faulon, J.-L. (2018). Extended Metabolic Space Modeling. Synthetic Metabolic Pathways, 83–96. https://doi.org/10.1007/978-1-4939-7295-1_6

Carbonell, P., Jervis, A. J., Robinson, C. J., Yan, C., Dunstan, M., Swainston, N., Vinaixa, M., Hollywood, K. A., Currin, A., Rattray, N. J. W., Taylor, S., Spiess, R., Sung, R., Williams, A. R., Fellows, D., Stanford, N. J., Mulherin, P., Le Feuvre, R., Barran, P., … Scrutton, N. S. (2018). An automated Design-Build-Test-Learn pipeline for enhanced microbial production of fine chemicals. Communications Biology, 1(1). https://doi.org/10.1038/s42003-018-0076-9

Carbonell, P., Koch, M., Duigou, T., & Faulon, J.-L. (2018). Enzyme Discovery: Enzyme Selection and Pathway Design. Enzymes in Synthetic Biology, 3–27. https://doi.org/10.1016/bs.mie.2018.04.005

Duigou, T., du Lac, M., Carbonell, P., & Faulon, J.-L. (2018). RetroRules: a database of reaction rules for engineering biology. Nucleic Acids Research, 47(D1), D1229–D1235. https://doi.org/10.1093/nar/gky940

Jervis, A. J., Carbonell, P., Vinaixa, M., Dunstan, M. S., Hollywood, K. A., Robinson, C. J., Rattray, N. J. W., Yan, C., Swainston, N., Currin, A., Sung, R., Toogood, H., Taylor, S., Faulon, J.-L., Breitling, R., Takano, E., & Scrutton, N. S. (2018). Machine Learning of Designed Translational Control Allows Predictive Pathway Optimization in Escherichia coli. ACS Synthetic Biology, 8(1), 127–136. https://doi.org/10.1021/acssynbio.8b00398

Swainston, N., Batista-Navarro, R., Carbonell, P., Dobson, P. D., Dunstan, M., Jervis, A. J., Vinaixa, M., Williams, A. R., Ananiadou, S., Faulon, J.-L., Mendes, P., Kell, D. B., Scrutton, N. S., & Breitling, R. (2017). biochem4j: Integrated and extensible biochemical knowledge through graph databases. PLOS ONE, 12(7), e0179130. https://doi.org/10.1371/journal.pone.0179130

Swainston, N., Dunstan, M., Jervis, A. J., Robinson, C. J., Carbonell, P., Williams, A. R., Faulon, J.-L., Scrutton, N. S., & Kell, D. B. (2017). PartsGenie: an integrated tool for optimising and sharing synthetic biology parts. https://doi.org/10.1101/189357

Koch, M., Duigou, T., Carbonell, P., & Faulon, J.-L. (2017). Molecular structures enumeration and virtual screening in the chemical space with RetroPath2.0. Journal of Cheminformatics, 9(1). https://doi.org/10.1186/s13321-017-0252-9

Delépine, B., Libis, V., Carbonell, P., & Faulon, J.-L. (2016). SensiPath: computer-aided design of sensing-enabling metabolic pathways. Nucleic Acids Research, 44(W1), W226–W231. https://doi.org/10.1093/nar/gkw305

Mellor, J., Grigoras, I., Carbonell, P., & Faulon, J.-L. (2016). Semisupervised Gaussian Process for Automated Enzyme Search. ACS Synthetic Biology, 5(6), 518–528. https://doi.org/10.1021/acssynbio.5b00294

Carbonell, P., Currin, A., Jervis, A. J., Rattray, N. J. W., Swainston, N., Yan, C., Takano, E., & Breitling, R. (2016). Bioinformatics for the synthetic biology of natural products: integrating across the Design–Build–Test cycle. Natural Product Reports, 33(8), 925–932. https://doi.org/10.1039/c6np00018e

Carbonell, P., Currin, A., Dunstan, M., Fellows, D., Jervis, A., Rattray, N. J. W., Robinson, C. J., Swainston, N., Vinaixa, M., Williams, A., Yan, C., Barran, P., Breitling, R., Chen, G. G.-Q., Faulon, J.-L., Goble, C., Goodacre, R., Kell, D. B., Feuvre, R. L., … Turner, N. J. (2016). SYNBIOCHEM–a SynBio foundry for the biosynthesis and sustainable production of fine and speciality chemicals. Biochemical Society Transactions, 44(3), 675–677. https://doi.org/10.1042/bst20160009

Carbonell, P., Gök, A., Shapira, P., & Faulon, J. (2016). Mapping the patent landscape of synthetic biology for fine chemical production pathways. Microbial Biotechnology, 9(5), 687–695. Portico. https://doi.org/10.1111/1751-7915.12401

RA, L. F., P, C., A, C., M, D., D, F., AJ, J., NJW, R., CJ, R., N, S., M, V., A, W., C, Y., P, B., R, B., GG, C., JL, F., C, G., R, G., DB, K., … NJ, T. (2016). SYNBIOCHEM Synthetic Biology Research Centre, Manchester – A UK foundry for fine and speciality chemicals production. Synthetic and Systems Biotechnology, 1(4), 271–275. https://doi.org/10.1016/j.synbio.2016.07.001

Trosset, J.-Y., & Carbonell, P. (2015). Synthetic biology for pharmaceutical drug discovery. Drug Design, Development and Therapy, 6285. https://doi.org/10.2147/dddt.s58049

Martiny, V. Y., Carbonell, P., Chevillard, F., Moroy, G., Nicot, A. B., Vayer, P., Villoutreix, B. O., & Miteva, M. A. (2015). Integrated structure- and ligand-basedin silicoapproach to predict inhibition of cytochrome P450 2D6. Bioinformatics, 31(24), 3930–3937. https://doi.org/10.1093/bioinformatics/btv486

Ceroni, F., Carbonell, P., François, J.-M., & Haynes, K. A. (2015). Editorial – Synthetic Biology: Engineering Complexity and Refactoring Cell Capabilities. Frontiers in Bioengineering and Biotechnology, 3. https://doi.org/10.3389/fbioe.2015.00120

Fehér, T., Libis, V., Carbonell, P., & Faulon, J.-L. (2015). A Sense of Balance: Experimental Investigation and Modeling of a Malonyl-CoA Sensor in Escherichia coli. Frontiers in Bioengineering and Biotechnology, 3. https://doi.org/10.3389/fbioe.2015.00046

Carbonell, P., Parutto, P., Herisson, J., Pandit, S. B., & Faulon, J.-L. (2014). XTMS: pathway design in an eXTended metabolic space. Nucleic Acids Research, 42(W1), W389–W394. https://doi.org/10.1093/nar/gku362

Delépine, B., Carbonell, P., & Faulon, J.-L. (2014). XTMS in Action: Retrosynthetic Design in the Extended Metabolic Space of Heterologous Pathways for High-Value Compounds. Computational Methods in Systems Biology, 256–259. https://doi.org/10.1007/978-3-319-12982-2_21

Carbonell, P., & Trosset, J.-Y. (2014). Overcoming drug resistance through in silico prediction. Drug Discovery Today: Technologies, 11, 101–107. https://doi.org/10.1016/j.ddtec.2014.03.012

Fernández-Castané, A., Fehér, T., Carbonell, P., Pauthenier, C., & Faulon, J.-L. (2014). Computer-aided design for metabolic engineering. Journal of Biotechnology, 192, 302–313. https://doi.org/10.1016/j.jbiotec.2014.03.029

Fehér, T., Planson, A., Carbonell, P., Fernández‐Castané, A., Grigoras, I., Dariy, E., Perret, A., & Faulon, J. (2014). Validation of RetroPath, a computer‐aided design tool for metabolic pathway engineering. Biotechnology Journal, 9(11), 1446–1457. Portico. https://doi.org/10.1002/biot.201400055

Carbonell, P., & Trosset, J.-Y. (2014). Computational Protein Design Methods for Synthetic Biology. Computational Methods in Synthetic Biology, 3–21. https://doi.org/10.1007/978-1-4939-1878-2_1

Carbonell, P., Carlsson, L., & Faulon, J.-L. (2013). Stereo Signature Molecular Descriptor. Journal of Chemical Information and Modeling, 53(4), 887–897. https://doi.org/10.1021/ci300584r

Carbonell, P., Planson, A.-G., & Faulon, J.-L. (2013). Retrosynthetic Design of Heterologous Pathways. Systems Metabolic Engineering, 149–173. https://doi.org/10.1007/978-1-62703-299-5_9

Martiny, V. Y., Carbonell, P., Lagorce, D., Villoutreix, B. O., Moroy, G., & Miteva, M. A. (2013). In Silico Mechanistic Profiling to Probe Small Molecule Binding to Sulfotransferases. PLoS ONE, 8(9), e73587. https://doi.org/10.1371/journal.pone.0073587

Xu, S. S.-D., Ying, H., Carbonell, P., Lee, C.-H., & Wu, W.-S. (2013). Fuzzy Logic Applications in Control Theory and Systems Biology. Advances in Fuzzy Systems, 2013, 1–1. https://doi.org/10.1155/2013/504728

Carbonell, P., Parutto, P., Baudier, C., Junot, C., & Faulon, J.-L. (2013). Retropath: Automated Pipeline for Embedded Metabolic Circuits. ACS Synthetic Biology, 3(8), 565–577. https://doi.org/10.1021/sb4001273

Carbonell, P., Fichera, D., Pandit, S. B., & Faulon, J.-L. (2012). Enumerating metabolic pathways for the production of heterologous target chemicals in chassis organisms. BMC Systems Biology, 6(1). https://doi.org/10.1186/1752-0509-6-10

Carbonell, P., Lecointre, G., & Faulon, J.-L. (2011). Origins of Specificity and Promiscuity in Metabolic Networks. Journal of Biological Chemistry, 286(51), 43994–44004. https://doi.org/10.1074/jbc.m111.274050

Planson, A., Carbonell, P., Grigoras, I., & Faulon, J. (2011). Engineering antibiotic production and overcoming bacterial resistance. Biotechnology Journal, 6(7), 812–825. Portico. https://doi.org/10.1002/biot.201100085

Carbonell, P., Planson, A.-G., Fichera, D., & Faulon, J.-L. (2011). A retrosynthetic biology approach to metabolic pathway design for therapeutic production. BMC Systems Biology, 5(1). https://doi.org/10.1186/1752-0509-5-122

Planson, A., Carbonell, P., Paillard, E., Pollet, N., & Faulon, J. (2011). Compound toxicity screening and structure–activity relationship modeling in Escherichia coli. Biotechnology and Bioengineering, 109(3), 846–850. Portico. https://doi.org/10.1002/bit.24356

Faulon, J.-L., & Bender, A. (2010). Handbook of Chemoinformatics Algorithms. Chapman and Hall/CRC. https://doi.org/10.1201/9781420082999

Carbonell, P., & Faulon, J.-L. (2010). Molecular signatures-based prediction of enzyme promiscuity. Bioinformatics, 26(16), 2012–2019. https://doi.org/10.1093/bioinformatics/btq317

Carbonell, P., & Sol, A. del. (2009). Methyl side-chain dynamics prediction based on protein structure. Bioinformatics, 25(19), 2552–2558. https://doi.org/10.1093/bioinformatics/btp463

Carbonell, P., Nussinov, R., & del Sol, A. (2009). Energetic determinants of protein binding specificity: Insights into protein interaction networks. PROTEOMICS, 9(7), 1744–1753. Portico. https://doi.org/10.1002/pmic.200800425

del Sol, A., & Carbonell, P. (2007). The Modular Organization of Domain Structures: Insights into Protein–Protein Binding. PLoS Computational Biology, 3(12), e239. https://doi.org/10.1371/journal.pcbi.0030239

Colinge, J., Masselot, A., Carbonell, P., & Appel, R. D. (2006). InSilicoSpectro:  An Open-Source Proteomics Library. Journal of Proteome Research, 5(3), 619–624. https://doi.org/10.1021/pr0504236

Carbonell, P., Jiang, Z.-P., & Panwar, S. (2002). FUZZY TCP: A PRELIMINARY STUDY. IFAC Proceedings Volumes, 35(1), 205–210. https://doi.org/10.3182/20020721-6-es-1901.00687

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