The Chemometrics for Environmental Omics group focuses on the development and application of chemometric (data analysis) and analytical tools for the study of problems of environmental interest. Main research lines include the development of chemometric approaches to analyse datasets coming from diverse analytical platforms, the application of these chemometric data analysis methods to evaluate the metabolomic effects of chemical pollutants and global change stressors on environmentally relevant organisms, and the analysis of environmental data sets (i.e. monitoring studies on air, surface waters, sediments and soils) to retrieve information regarding the identification, resolution, and apportionment of pollution sources and their environmental impact.
Analysis packages (R, Python, etc.), Annotation tools, Artificial Intelligence, Bioinformatics Software and Tools, Data Analysis, Data Visualization, Deep Learning in Biology, Desktop application, Experimental design, Image analysis, Machine Learning in Biology, Metabolite annotation, Metabolite Biomarker Identification, Metabolome profiling, Metabolomics, Multivariate statistics, Natural Language Processing (NLP), Non-parametric statistics, Omics, Statistical Methods for Biology, Text mining
Publications
Menéndez-Pedriza, A., Molina-Millán, L., Cuypers, E., Cillero-Pastor, B., Navarro-Martín, L., Jaumot, J., & Heeren, R. M. A. (2025). Advancing environmental toxicology: The role of mass spectrometry imaging. Trends in Environmental Analytical Chemistry, 45, e00253. https://doi.org/10.1016/j.teac.2024.e00253
Pyambri, M., Jaumot, J., & Bedia, C. (2025). Toxicity Assessment of Organophosphate Flame Retardants Using New Approach Methodologies. Toxics, 13(4), 297. https://doi.org/10.3390/toxics13040297
Menéndez-Pedriza, A., Blázquez, M., Navarro-Martín, L., & Jaumot, J. (2025). Mapping shared and unique features in spatial transcriptomics through multivariate curve resolution. Microchemical Journal, 212, 113189. https://doi.org/10.1016/j.microc.2025.113189
Perez-Lopez, C., Ginebreda, A., Jaumot, J., Yamamoto, F. Y., Barcelo, D., & Tauler, R. (2024). MSident: Straightforward identification of chemical compounds from MS-resolved spectra. Chemometrics and Intelligent Laboratory Systems, 245, 105063. https://doi.org/10.1016/j.chemolab.2024.105063
Zöhrer, B., Gómez, C., Jaumot, J., Idborg, H., Torekov, S. S., Wheelock, Å. M., Wheelock, C. E., & Checa, A. (2024). Cohort-based strategies as an in-house tool to evaluate and improve phenotyping robustness of LC–MS/MS lipidomics platforms. Analytical and Bioanalytical Chemistry, 416(25), 5485–5496. https://doi.org/10.1007/s00216-024-05404-8
Pérez-Cova, M., Bedia, C., Checa, A., Meister, I., Tauler, R., Wheelock, C. E., & Jaumot, J. (2024). Metabolomic and sphingolipidomic profiling of human hepatoma cells exposed to widely used pharmaceuticals. Journal of Pharmaceutical and Biomedical Analysis, 249, 116378. https://doi.org/10.1016/j.jpba.2024.116378
Pyambri, M., Lacorte, S., Jaumot, J., & Bedia, C. (2023). Effects of Indoor Dust Exposure on Lung Cells: Association of Chemical Composition with Phenotypic and Lipid Changes in a 3D Lung Cancer Cell Model. Environmental Science & Technology, 57(49), 20532–20541. https://doi.org/10.1021/acs.est.3c07573
Menéndez-Pedriza, A., Navarro-Martín, L., & Jaumot, J. (2023). A novel multivariate curve resolution based strategy for multi-omic integration of toxicological data. Chemometrics and Intelligent Laboratory Systems, 242, 104999. https://doi.org/10.1016/j.chemolab.2023.104999
Pérez-Cova, M., Platikanov, S., Tauler, R., & Jaumot, J. (2022). Quantification Strategies for Two-Dimensional Liquid Chromatography Datasets Using Regions of Interest and Multivariate Curve Resolution Approaches. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4074787
Menéndez-Pedriza, A., Jaumot, J., & Bedia, C. (2022). Lipidomic analysis of single and combined effects of polyethylene microplastics and polychlorinated biphenyls on human hepatoma cells. Journal of Hazardous Materials, 421, 126777. https://doi.org/10.1016/j.jhazmat.2021.126777
Pérez-Cova, M., Platikanov, S., Stoll, D. R., Tauler, R., & Jaumot, J. (2022). Comparison of Multivariate ANOVA-Based Approaches for the Determination of Relevant Variables in Experimentally Designed Metabolomic Studies. Molecules, 27(10), 3304. https://doi.org/10.3390/molecules27103304
Pérez-Cova, M., Tauler, R., & Jaumot, J. (2022). Adverse Effects of Arsenic Uptake in Rice Metabolome and Lipidome Revealed by Untargeted Liquid Chromatography Coupled to Mass Spectrometry (LC-MS) and Regions of Interest Multivariate Curve Resolution. Separations, 9(3), 79. https://doi.org/10.3390/separations9030079
Jaumot, J., & Bedia, C. (2021). Introduction to Data Analysis in Omics Sciences. Comprehensive Foodomics, 226–240. https://doi.org/10.1016/b978-0-08-100596-5.22901-6
Pérez-Cova, M., Jaumot, J., & Tauler, R. (2021). Untangling comprehensive two-dimensional liquid chromatography data sets using regions of interest and multivariate curve resolution approaches. TrAC Trends in Analytical Chemistry, 137, 116207. https://doi.org/10.1016/j.trac.2021.116207
Pérez-Cova, M., Bedia, C., Stoll, D. R., Tauler, R., & Jaumot, J. (2021). MSroi: A pre-processing tool for mass spectrometry-based studies. Chemometrics and Intelligent Laboratory Systems, 215, 104333. https://doi.org/10.1016/j.chemolab.2021.104333
Pérez-Cova, M., Tauler, R., & Jaumot, J. (2020). Chemometrics in comprehensive two-dimensional liquid chromatography: A study of the data structure and its multilinear behavior. Chemometrics and Intelligent Laboratory Systems, 201, 104009. https://doi.org/10.1016/j.chemolab.2020.104009
Jaumot, J., & Bedia, C. (2020). Mass Spectrometry Imaging: Chemometric Data Analysis. Comprehensive Chemometrics, 381–394. https://doi.org/10.1016/b978-0-12-409547-2.14599-8
Pérez-Cova, M., Tauler, R., & Jaumot, J. (2020). Two-Dimensional Liquid Chromatography in Metabolomics and Lipidomics. Metabolomics, 25–47. https://doi.org/10.1007/978-1-0716-0864-7_3
Navarro-Reig, M., Tauler, R., Iriondo-Frias, G., & Jaumot, J. (2019). Untargeted lipidomic evaluation of hydric and heat stresses on rice growth. Journal of Chromatography B, 1104, 148–156. https://doi.org/10.1016/j.jchromb.2018.11.018
Gorrochategui, E., Jaumot, J., & Tauler, R. (2019). ROIMCR: a powerful analysis strategy for LC-MS metabolomic datasets. BMC Bioinformatics, 20(1). https://doi.org/10.1186/s12859-019-2848-8
Felten, J., Hall, H., Jaumot, J., Tauler, R., de Juan, A., & Gorzsás, A. (2019). Addendum: Vibrational spectroscopic image analysis of biological material using multivariate curve resolution–alternating least squares (MCR-ALS). Nature Protocols, 14(10), 3032–3032. https://doi.org/10.1038/s41596-019-0196-9
Gilabert, A., Geraudie, P., Jaumot, J., & Porte, C. (2019). Partial characterization of the lipidome of the cold-water scallop, Chlamys islandica. Environmental Science and Pollution Research, 27(2), 1475–1484. https://doi.org/10.1007/s11356-019-06751-1
Benavente, F., Pero-Gascon, R., Pont, L., Jaumot, J., Barbosa, J., & Sanz-Nebot, V. (2018). Identification of antihypertensive peptides in nutraceuticals by capillary electrophoresis-mass spectrometry. Journal of Chromatography A, 1579, 129–137. https://doi.org/10.1016/j.chroma.2018.10.018
Navarro‐Reig, M., Bedia, C., Tauler, R., & Jaumot, J. (2018). Chemometric Strategies for Peak Detection and Profiling from Multidimensional Chromatography. PROTEOMICS, 18(18). Portico. https://doi.org/10.1002/pmic.201700327
Ortiz-Villanueva, E., Jaumot, J., Martínez, R., Navarro-Martín, L., Piña, B., & Tauler, R. (2018). Assessment of endocrine disruptors effects on zebrafish (Danio rerio) embryos by untargeted LC-HRMS metabolomic analysis. Science of The Total Environment, 635, 156–166. https://doi.org/10.1016/j.scitotenv.2018.03.369
Navarro-Reig, M., Jaumot, J., & Tauler, R. (2018). An untargeted lipidomic strategy combining comprehensive two-dimensional liquid chromatography and chemometric analysis. Journal of Chromatography A, 1568, 80–90. https://doi.org/10.1016/j.chroma.2018.07.017
Pont, L., Sanz-Nebot, V., Vilaseca, M., Jaumot, J., Tauler, R., & Benavente, F. (2018). A chemometric approach for characterization of serum transthyretin in familial amyloidotic polyneuropathy type I (FAP-I) by electrospray ionization-ion mobility mass spectrometry. Talanta, 181, 87–94. https://doi.org/10.1016/j.talanta.2017.12.072
Navarro-Reig, M., Jaumot, J., Baglai, A., Vivó-Truyols, G., Schoenmakers, P. J., & Tauler, R. (2017). Untargeted Comprehensive Two-Dimensional Liquid Chromatography Coupled with High-Resolution Mass Spectrometry Analysis of Rice Metabolome Using Multivariate Curve Resolution. Analytical Chemistry, 89(14), 7675–7683. https://doi.org/10.1021/acs.analchem.7b01648
Lyonnais, S., Tarrés-Solé, A., Rubio-Cosials, A., Cuppari, A., Brito, R., Jaumot, J., Gargallo, R., Vilaseca, M., Silva, C., Granzhan, A., Teulade-Fichou, M.-P., Eritja, R., & Solà, M. (2017). The human mitochondrial transcription factor A is a versatile G-quadruplex binding protein. Scientific Reports, 7(1). https://doi.org/10.1038/srep43992
Navarro-Reig, M., Ortiz-Villanueva, E., Tauler, R., & Jaumot, J. (2017). Modelling of Hydrophilic Interaction Liquid Chromatography Stationary Phases Using Chemometric Approaches. Metabolites, 7(4), 54. https://doi.org/10.3390/metabo7040054
Navarro-Reig, M., Jaumot, J., Piña, B., Moyano, E., Galceran, M. T., & Tauler, R. (2017). Metabolomic analysis of the effects of cadmium and copper treatment in Oryza sativa L. using untargeted liquid chromatography coupled to high resolution mass spectrometry and all-ion fragmentation. Metallomics, 9(6), 660–675. https://doi.org/10.1039/c6mt00279j
Ortiz-Villanueva, E., Navarro-Martín, L., Jaumot, J., Benavente, F., Sanz-Nebot, V., Piña, B., & Tauler, R. (2017). Metabolic disruption of zebrafish (Danio rerio) embryos by bisphenol A. An integrated metabolomic and transcriptomic approach. Environmental Pollution, 231, 22–36. https://doi.org/10.1016/j.envpol.2017.07.095
Ortiz-Villanueva, E., Benavente, F., Piña, B., Sanz-Nebot, V., Tauler, R., & Jaumot, J. (2017). Knowledge integration strategies for untargeted metabolomics based on MCR-ALS analysis of CE-MS and LC-MS data. Analytica Chimica Acta, 978, 10–23. https://doi.org/10.1016/j.aca.2017.04.049
Lyonnais, S., Tarrés-Solé, A., Rubio-Cosials, A., Cuppari, A., Brito, R., Jaumot, J., Gargallo, R., Vilaseca, M., Silva, C., Granzhan, A., Teulade-Fichou, M.-P., Eritja, R., & Solà, M. (2017). Correction: Corrigendum: The human mitochondrial transcription factor A is a versatile G-quadruplex binding protein. Scientific Reports, 7(1). https://doi.org/10.1038/srep45948
Ortiz-Villanueva, E., Navarro-Reig, M., Jaumot, J., & Tauler, R. (2017). Chemometric evaluation of hydrophilic interaction liquid chromatography stationary phases: resolving complex mixtures of metabolites. Analytical Methods, 9(5), 774–785. https://doi.org/10.1039/c6ay02976k
Bedia, C., Tauler, R., & Jaumot, J. (2017). Analysis of multiple mass spectrometry images from different Phaseolus vulgaris samples by multivariate curve resolution. Talanta, 175, 557–565. https://doi.org/10.1016/j.talanta.2017.07.087
Pont, L., Benavente, F., Jaumot, J., Tauler, R., Alberch, J., Ginés, S., Barbosa, J., & Sanz‐Nebot, V. (2016). Metabolic profiling for the identification of Huntington biomarkers by on‐line solid‐phase extraction capillary electrophoresis mass spectrometry combined with advanced data analysis tools. ELECTROPHORESIS, 37(5–6), 795–808. Portico. https://doi.org/10.1002/elps.201500378
Gorrochategui, E., Jaumot, J., Lacorte, S., & Tauler, R. (2016). Data analysis strategies for targeted and untargeted LC-MS metabolomic studies: Overview and workflow. TrAC Trends in Analytical Chemistry, 82, 425–442. https://doi.org/10.1016/j.trac.2016.07.004
Bedia, C., Tauler, R., & Jaumot, J. (2016). Compression strategies for the chemometric analysis of mass spectrometry imaging data. Journal of Chemometrics, 30(10), 575–588. Portico. https://doi.org/10.1002/cem.2821
Navarro-Reig, M., Jaumot, J., van Beek, T. A., Vivó-Truyols, G., & Tauler, R. (2016). Chemometric analysis of comprehensive LC×LC-MS data: Resolution of triacylglycerol structural isomers in corn oil. Talanta, 160, 624–635. https://doi.org/10.1016/j.talanta.2016.08.005
Jaumot, J., Navarro, A., Faria, M., Barata, C., Tauler, R., & Piña, B. (2015). qRT-PCR evaluation of the transcriptional response of zebra mussel to heavy metals. BMC Genomics, 16(1). https://doi.org/10.1186/s12864-015-1567-4
Felten, J., Hall, H., Jaumot, J., Tauler, R., de Juan, A., & Gorzsás, A. (2015). Vibrational spectroscopic image analysis of biological material using multivariate curve resolution–alternating least squares (MCR-ALS). Nature Protocols, 10(2), 217–240. https://doi.org/10.1038/nprot.2015.008
Jaumot, J., & Tauler, R. (2015). Potential use of multivariate curve resolution for the analysis of mass spectrometry images. The Analyst, 140(3), 837–846. https://doi.org/10.1039/c4an00801d
Bedia, C., Dalmau, N., Jaumot, J., & Tauler, R. (2015). Phenotypic malignant changes and untargeted lipidomic analysis of long-term exposed prostate cancer cells to endocrine disruptors. Environmental Research, 140, 18–31. https://doi.org/10.1016/j.envres.2015.03.014
Jaumot, J., de Juan, A., & Tauler, R. (2015). MCR-ALS GUI 2.0: New features and applications. Chemometrics and Intelligent Laboratory Systems, 140, 1–12. https://doi.org/10.1016/j.chemolab.2014.10.003
Checa, A., Bedia, C., & Jaumot, J. (2015). Lipidomic data analysis: Tutorial, practical guidelines and applications. Analytica Chimica Acta, 885, 1–16. https://doi.org/10.1016/j.aca.2015.02.068
Navarro-Reig, M., Jaumot, J., García-Reiriz, A., & Tauler, R. (2015). Evaluation of changes induced in rice metabolome by Cd and Cu exposure using LC-MS with XCMS and MCR-ALS data analysis strategies. Analytical and Bioanalytical Chemistry, 407(29), 8835–8847. https://doi.org/10.1007/s00216-015-9042-2
Dalmau, N., Jaumot, J., Tauler, R., & Bedia, C. (2015). Epithelial-to-mesenchymal transition involves triacylglycerol accumulation in DU145 prostate cancer cells. Molecular BioSystems, 11(12), 3397–3406. https://doi.org/10.1039/c5mb00413f
Ortiz‐Villanueva, E., Jaumot, J., Benavente, F., Piña, B., Sanz‐Nebot, V., & Tauler, R. (2015). Combination of CE‐MS and advanced chemometric methods for high‐throughput metabolic profiling. ELECTROPHORESIS, 36(18), 2324–2335. Portico. https://doi.org/10.1002/elps.201500027
Benabou, S., Ferreira, R., Aviñó, A., González, C., Lyonnais, S., Solà, M., Eritja, R., Jaumot, J., & Gargallo, R. (2014). Solution equilibria of cytosine- and guanine-rich sequences near the promoter region of the n-myc gene that contain stable hairpins within lateral loops. Biochimica et Biophysica Acta (BBA) - General Subjects, 1840(1), 41–52. https://doi.org/10.1016/j.bbagen.2013.08.028
de Juan, A., Jaumot, J., & Tauler, R. (2014). Multivariate Curve Resolution (MCR). Solving the mixture analysis problem. Anal. Methods, 6(14), 4964–4976. https://doi.org/10.1039/c4ay00571f
Igne, B., Juan, A. de, Jaumot, J., Lallemand, J., Preys, S., Drennen, J. K., & Anderson, C. A. (2014). Modeling strategies for pharmaceutical blend monitoring and end-point determination by near-infrared spectroscopy. International Journal of Pharmaceutics, 473(1–2), 219–231. https://doi.org/10.1016/j.ijpharm.2014.06.061
Jaumot, J., Igne, B., Anderson, C. A., Drennen, J. K., & de Juan, A. (2013). Blending process modeling and control by multivariate curve resolution. Talanta, 117, 492–504. https://doi.org/10.1016/j.talanta.2013.09.037
Manaye, S., Eritja, R., Aviñó, A., Jaumot, J., & Gargallo, R. (2012). Porphyrin binding mechanism is altered by protonation at the loops in G-quadruplex DNA formed near the transcriptional activation site of the human c-kit gene. Biochimica et Biophysica Acta (BBA) - General Subjects, 1820(12), 1987–1996. https://doi.org/10.1016/j.bbagen.2012.09.006
Jaumot, J., & Gargallo, R. (2012). Experimental Methods for Studying the Interactions between G-Quadruplex Structures and Ligands. Current Pharmaceutical Design, 18(14), 1900–1916. https://doi.org/10.2174/138161212799958486
Ruiz-Castelar, S., Checa, A., Gargallo, R., & Jaumot, J. (2012). Combination of chromatographic and chemometric methods to study the interactions between DNA strands. Analytica Chimica Acta, 722, 34–42. https://doi.org/10.1016/j.aca.2012.02.005
Jalali-Heravi, M., Parastar, H., Kamalzadeh, M., Tauler, R., & Jaumot, J. (2010). MCRC software: A tool for chemometric analysis of two-way chromatographic data. Chemometrics and Intelligent Laboratory Systems, 104(2), 155–171. https://doi.org/10.1016/j.chemolab.2010.08.002
Jaumot, J., Piña, B., & Tauler, R. (2010). Application of multivariate curve resolution to the analysis of yeast genome-wide screens. Chemometrics and Intelligent Laboratory Systems, 104(1), 53–64. https://doi.org/10.1016/j.chemolab.2010.04.004
Jaumot, J., Eritja, R., & Gargallo, R. (2010). Chemical equilibria studies using multivariate analysis methods. Analytical and Bioanalytical Chemistry, 399(6), 1983–1997. https://doi.org/10.1007/s00216-010-4310-7
del Toro, M., Bucek, P., Aviñó, A., Jaumot, J., González, C., Eritja, R., & Gargallo, R. (2009). Targeting the G-quadruplex-forming region near the P1 promoter in the human BCL-2 gene with the cationic porphyrin TMPyP4 and with the complementary C-rich strand. Biochimie, 91(7), 894–902. https://doi.org/10.1016/j.biochi.2009.04.012
Bucek, P., Jaumot, J., Aviñó, A., Eritja, R., & Gargallo, R. (2009). pH‐Modulated Watson–Crick Duplex–Quadruplex Equilibria of Guanine‐Rich and Cytosine‐Rich DNA Sequences 140 Base Pairs Upstream of the c‐kit Transcription Initiation Site. Chemistry – A European Journal, 15(46), 12663–12671. Portico. https://doi.org/10.1002/chem.200901631
Jaumot, J., Eritja, R., Navea, S., & Gargallo, R. (2009). Classification of nucleic acids structures by means of the chemometric analysis of circular dichroism spectra. Analytica Chimica Acta, 642(1–2), 117–126. https://doi.org/10.1016/j.aca.2008.12.052
Jaumot, J. (2006). Resolution of a structural competition involving dimeric G-quadruplex and its C-rich complementary strand. Nucleic Acids Research, 34(1), 206–216. https://doi.org/10.1093/nar/gkj421
Jaumot, J., Tauler, R., & Gargallo, R. (2006). Exploratory data analysis of DNA microarrays by multivariate curve resolution. Analytical Biochemistry, 358(1), 76–89. https://doi.org/10.1016/j.ab.2006.07.028
Jaumot, J., Gargallo, R., de Juan, A., & Tauler, R. (2005). A graphical user-friendly interface for MCR-ALS: a new tool for multivariate curve resolution in MATLAB. Chemometrics and Intelligent Laboratory Systems, 76(1), 101–110. https://doi.org/10.1016/j.chemolab.2004.12.007
Jaumot, J., Gargallo, R., & Tauler, R. (2004). Noise propagation and error estimations in multivariate curve resolution alternating least squares using resampling methods. Journal of Chemometrics, 18(7–8), 327–340. Portico. https://doi.org/10.1002/cem.876
Plankensteiner, K., Righi, A., Rode, B. M., Gargallo, R., Jaumot, J., & Tauler, R. (2004). Indications towards a stereoselectivity of the salt-induced peptide formation reaction. Inorganica Chimica Acta, 357(3), 649–656. https://doi.org/10.1016/j.ica.2003.06.012
Jaumot, J., Vives, M., & Gargallo, R. (2004). Application of multivariate resolution methods to the study of biochemical and biophysical processes. Analytical Biochemistry, 327(1), 1–13. https://doi.org/10.1016/j.ab.2003.12.028
Jaumot, J., Marchán, V., Gargallo, R., Grandas, A., & Tauler, R. (2004). Multivariate Curve Resolution Applied to the Analysis and Resolution of Two-Dimensional [1H,15N] NMR Reaction Spectra. Analytical Chemistry, 76(23), 7094–7101. https://doi.org/10.1021/ac049509t
Jaumot, J., Vives, M., Gargallo, R., & Tauler, R. (2003). Multivariate resolution of NMR labile signals by means of hard- and soft-modelling methods. Analytica Chimica Acta, 490(1–2), 253–264. https://doi.org/10.1016/s0003-2670(03)00092-8
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