Diogo Alexandre Rosa Serra Latino

Curriculum Vitae

Zurich

October 2017 Contents

1 Personal Information 4

2 Academic Degrees 4

3 Education 4

4 Professional Pathway 5

5 Scientific and Research Experience 5 5.1 Summary ...... 5

6 Scientific Activity 6 6.1 Publications ...... 6 6.1.1 Thesis and Dissertations ...... 6 6.1.2 Book Chapters ...... 6 6.1.3 Papers in International Scientific Periodicals with Referees ...... 7 6.1.4 Papers in National Scientific Periodicals with Referees ...... 9 6.1.5 Other Publications with Referees ...... 9 6.2 Oral and Poster Communications ...... 10 6.2.1 Oral Communications in Scientific Conferences ...... 10 6.2.2 Other Oral Communications ...... 11 6.2.3 Posters in Scientific Conferences ...... 11 6.3 Participation in Projects ...... 14 6.4 Honours and Awards ...... 15 6.5 Collaborations with other Groups ...... 15 6.6 Collaborations with Industry ...... 16

7 Teaching Activity 16 7.1 Students Supervision ...... 16 7.1.1 Master Thesis ...... 16 7.1.2 Research Dissertation for Graduation ...... 16 7.2 Undergraduate Courses ...... 17 7.2.1 In Dep. of Chemistry and Biochemistry, Faculty of Sciences, University of Lisbon . 17 7.2.2 In Dep. of Chemistry, Faculty of Sciences and Technology, New University of Lisbon 17 7.3 Postgraduate Courses ...... 17 7.3.1 In Dep. of Chemistry and Biochemistry, Faculty of Sciences, University of Lisbon . 17 7.3.2 In Dep. of Chemistry, Faculty of Sciences and Technology, New University of Lisbon 18 7.4 Other Courses ...... 18 7.4.1 In Faculty of Pharmacy, University of Lisbon ...... 18

8 Participation in Organizing Committees of Scientific Conferences 18

2 9 Chemoinformatics Skills 18 9.1 (scientific research) ...... 18 9.1.1 Molecular descriptors calculation ...... 18 9.1.2 Optimization of molecular structures ...... 19 9.1.3 machine learning and/ or statistical methods ...... 19 9.1.4 Others ...... 20

10 Languages 20

3 Curriculum Vitae

Diogo Alexandre Rosa Serra Latino

1 Personal Information

Name: Diogo Alexandre Rosa Serra Latino

Date of Birth: May 3, 1979 Birth Place: S. Sebasti˜aoda Pedreira, Lisbon, Portugal

Identity Card nº: 11521592 Marital Status: Single Nationality: Portuguese

E-mail: [email protected] [email protected]

Personal Pages: https://www.linkedin.com/pub/diogo-latino/42/912/25a https://www.researchgate.net/profile/Diogo Latino/ http://www.eawag.ch/about/personen/homepages/latinodi/index EN

Scientific Research Areas: Chemoinformatics Organic Chemistry, Physical Chemistry

2 Academic Degrees

ˆ Licenciatura in Chemistry, Faculty of Sciences, University of Lisbon, 2003.

ˆ PhD in Chemistry (Organic Chemistry / Chemoinformatics), New University of Lisbon, 2008.

3 Education

ˆ Licenciatura in Chemistry, Department of Chemistry and Biochemistry, Faculty of Sci- ences, University of Lisbon, 2003, final classification of 16 (out of 20).

Research Dissertation for the Graduation in Chemistry: Title: Application of Artificial Neural Networks to Chemical Analysis and Reactivity. Local: Molecular Simulation Group, Department of Chemistry and Biochemistry, Faculty of Sciences, University of Lisbon.

4 Supervisors: Prof. Fernando M. S. S. Fernandes e Prof. Filomena F. M. Freitas. Classification: 20 out of 20.

ˆ PhD in Chemistry (Organic Chemistry / Chemoinformatics)

Title: “Automatic Learning for the Classification of Chemical Reactions and in Statistical Ther- modynamics”. Scientific Domain: Chemoinformatics. Host Institutions: Faculty of Sciences and Technology, New University of Lisbon and Faculty of Sciences, University of Lisbon. Supervisors: Prof. Jo˜aoAires-de-Sousa (FCTUNL), Prof. Fernando M. S. S. Fernandes e Prof. Filomena F. M. Freitas (FCUL). Final Classification: Approved, by unamimity, 2008.

ˆ Post-Graduation in Analysis and Risk Management Nova IMS (Nova Information Management School), New University of Lisbon, 2014.

4 Professional Pathway

ˆ 2001 - 2006: Researcher, CECUL (Centro de Electroqu´ımica e Cin´etica da Universidade de Lisboa), Faculty of Sciences, University of Lisbon.

ˆ 2004 - 2014: Researcher, REQUIMTE (REde de QUImica e TEcnologia), Faculty of Sciences and Technology, New University of Lisbon.

ˆ 2007 - 2008, 2010 - 2014: Researcher, CCMM (Centro de Ciˆencias Moleculares e Materiais), Faculty of Sciences, University of Lisbon.

ˆ 2004 - 2008: PhD student, Chemistry of the Faculty of Sciences and Technology, New University of Lisbon.

ˆ 2008 - 2009: Post-Doc Researcher, SEAC (Safety & Environmental Assurance Centre), Unilever UK / Faculty of Sciences and Technology, New University of Lisbon.

ˆ 2010 - 2014: Post-Doc Researcher, REQUIMTE, Faculty of Sciences and Technology, New University of Lisbon.

ˆ Since 2014: Scientist, Eawag (Swiss Federal Institute of Aquatic Science and Technology).

5 Scientific and Research Experience

5.1 Summary

ˆ 15 years of experience in Chemoinformatics research.

ˆ Participation in the development of two methods for classification of chemical reactions.

ˆ Participation in the development of a new method for representation of chemical structures.

5 ˆ 35 publications - 1 research dissertation, 1 PhD Thesis, 1 book chapter, 23 papers in inter- national scientific journals with referees, 2 publications in national scientific journals with referees and 7 other publications with referees.

ˆ 45 communications (13 oral communications and 32 posters), 42 in scientific conferences and 3 in other seminars.

ˆ Experience with several software packages in the Chemoinformatics domain (see subsection “Software”).

ˆ Experience with the following machine learning methods: Kohonen Self-Organizing Maps, Feed-Forward Neural Networks, Counter-Propagation Neural Networks, Associative Neural Networks, Decision Trees, Regression Trees, Model Trees, Random Forests, Support Vector Machines.

ˆ Experience with several software packages for the optimization of molecular structures (MOPAC, , GAMESS).

ˆ Knowledge of different programming languages (C, C++, Fortran 77, F/Fortran 90/95).

ˆ Experience with chemical reactions databases and with a metabolic reactions and metabolic pathways database - KEGG (Kyoto Encyclopedia of Genes and Genomes) and BRENDA.

ˆ 2001-2014 collaboration in undergraduate and postgraduate courses of the Department of Chemistry and Biochemistry, Faculty of Sciences, University of Lisbon.

ˆ 2007-2014 collaboration in undergraduate and postgraduate courses of the Department of Chemistry, Faculty of Sciences and Technology, New University of Lisbon.

6 Scientific Activity

6.1 Publications

6.1.1 Thesis and Dissertations

1. D. A. R. S. Latino, “Application of Artificial Neural Networks to Chemical Analysis and Reactivity”, Research Dissertation for the Graduation in Chemistry, Faculty of Sciences, University of Lisbon, 2003. (http://elixir.dqb.fc.ul.pt/˜latino/relatorio estagio/)

2. D. A. R. S. Latino, “Automatic Learning for the Classification of Chemical Reactions and in Statistical Thermodynamics”, PhD Thesis, Faculty of Sciences and Technology, New University of Lisbon, 2008. (http://run.unl.pt/handle/10362/1752)

6.1.2 Book Chapters

1. D. A. R. S. Latino and J. Aires-de-Sousa,“Classification of Chemical Reactions and Chemoin- formatic Processing of Enzymatic Transformations”, in Chemoinformatics and Computa- tional Chemical Biology, Methods in Molecular Biology, vol. 672, Ed. Jurgen¨ Bajorath, Humana Press (Springer), 2011, 325-340.

6 6.1.3 Papers in International Scientific Periodicals with Referees

*Number of citations calculated using Web of Science and Google Scholar

1. D. A. R. S. Latino, J. Aires-de-Sousa, “Genome-Scale Classification of Metabolic Reactions: a Chemoinformatics Approach”, Angew. Chem. Int. Ed. 2006, 45, 2066-2069. Impact Factor: 10.232 (in 2006), 11.994 (in 2016). Citations: 30; 38.

2. D. A. R. S. Latino, J. Aires-de-Sousa, “Linking Databases of Chemical Reactions to NMR Data: An Exploration of 1H NMR - Based Reaction Classification”, Anal. Chem. 2007, 79, 854-862. Impact Factor: 5.287 (in 2007), 6.320 (in 2016). Citations: 7; 11.

3. D. A. R. S. Latino, F. F. M. Freitas, J. Aires-de-Sousa, F. M. S. S. Fernandes, “Neural Networks to Approach Potential Energy Surfaces. Application to a Simulation”, Int. J. Quantum Chem. 2007, 107, (11), 2120-2132. Impact Factor: 1.368 (in 2007), 2.920 (in 2016). Citations: 11; 16.

4. F. M. S. S. Fernandes, R. P. S. Fartaria, D. A. R. S. Latino, F. F. M. Freitas “Computer Simulation of Solution/Electrode Interfaces”, Port. Electrochim. Acta, ISSN 0872 - 1904, 2008, 26, (1), 1-13. Indexed in SCOPUS. Citations: 1; 1.

5. D. A. R. S. Latino, Q.-Y. Zhang, J. Aires-de-Sousa,“Genome-Scale Classification of Metabolic Reactions and Assignment of EC Numbers with Self-Organizing Maps”, Bioinformatics 2008, 24, 2236-2244. Impact Factor: 4.320 (in 2008), 6.990 (in 2016). Citations: 26; 35.

6. D. A. R. S. Latino, R. P. S. Fartaria, F. F. M. Freitas, J. Aires-de-Sousa, F. M. S. S. Fernandes, ”Mapping Potential Energy Surfaces by Neural Networks. The ethanol / Au (111) interface”, J. Electroanal. Chem. 2008, 624, 109-120. Impact Factor: 2.484 (in 2008), 3.012 (in 2016). Citations: 15; 18.

7. D. A. R. S. Latino, J. Aires-de-Sousa, “Assignment of EC Numbers to Enzymatic Reactions with MOLMAP Reaction Descriptors and Random Forests”, J. Chem. Inf. Model. 2009, 49 , 1839-1846. Impact Factor: 3.882 (in 2009), 3.760 (in 2016). Citations: 22; 33.

8. D. A. R. S. Latino, R. P. S. Fartaria, F. F. M. Freitas, J. Aires-de-Sousa, F. M. S. S. Fernandes, ”Approach to Potential Energy Surfaces by Neural Networks. A Review of Recent Work”, Int. J. Quantum Chem. 2010, 110, 432-445. Impact Factor: 1.302 (in 2010), 2.920 (in 2016). Citations: 6; 9.

9. F. Pereira, D. A. R. S. Latino, J. Aires-de-Sousa, “Estimation of Mayr Electrophilicity with a Quantitative Structure-Property Relationship Approach Using Empirical and DFT Descriptors”, J. Org. Chem. 2011, 76, 9312-9319. Impact Factor: 4.450 (in 2012), 4.849 (in 2016). Citations: 10; 13.

7 10. D. A. R. S. Latino, J. Aires-de-Sousa, “Automatic Perception of Chemical Similarities be- tween Metabolic Pathways”, Mol. Inf. 2012, 31, 135-144. Impact Factor: 2.338 (in 2012), 1.843 (in 2016). Citations: 1; 1.

11. X. Qu, D. A. R. S. Latino, J. Aires-de-Sousa, “A Big Data Approach to the Ultra-Fast Prediction of DFT-Calculated Bond Energies”, J. Cheminf. 2013, 5, 34. Impact Factor: 4.540 (in 2013), 4.220 (in 2016). Citations: 10; 15.

12. C. Ventura, D. Latino, F. Martins, “Comparison of Multiple Linear Regressions and Neural Networks Based QSAR Models for the Design of New Antitubercular Compounds”, Eur. J. Med. Chem. 2013, 70, 831-845. Impact Factor: 3.432 (in 2013), 4.519 (in 2016). Citations: 17; 21.

13. F. Pereira, D. A. R. S. Latino, S. P. Gaudˆencio, ”A Chemoinformatics Approach to the Dis- covery of Lead-Like from Marine and Microbial Sources En Route to Antitumor and Antibiotic Drugs”, Mar. Drugs 2014, 12, 757-778. Impact Factor: 2.853 (in 2014), 3.503 (in 2016). Citations: 7; 9.

14. D. A. R. S. Latino, J. Aires-de-Sousa, “Automatic NMR-Based Identification of Chemical Reaction Types in Mixtures of Co-Occurring Reactions”, PLoS ONE 2014, 9, e88499. Impact Factor: 3.234 (in 2014), 2.806 (in 2016). Citations: 0; 3.

15. Q.-Y Zhang, F. Zheng, R. Fartaria, D. A. R. S. Latino, X. Qu, T. Campos, T. Zhao, J. Aires-de-Sousa, “A QSPR Approach for the Fast Estimation of DFT/NBO Partial Atomic Charges”, Chemom. Intell. Lab. Syst. 2014, 134, 158-163. Impact Factor: 2.321 (in 2014), 2.303 (in 2016). Citations: 4; 4.

16. F. Martins, S. Santos, C. Ventura, R. Leit˜ao,L. Santos, S. Vitorino, M. Reis, V. Miranda, H. F. Correia, J. Aires-de-Sousa, V. Kovalishyn, D. A. R. S. Latino, J. Ramos, M. Viveiros, “Design, Synthesis and Biological Evaluation of Novel Isoniazid Derivatives with Potent anti-Tubercular Activity”, Eur. J. Med. Chem. 2014, 81, 119-138. Impact Factor: 3.447 (in 2014), 4.519 (in 2016). Citations: 32; 39.

17. G. Marcou, J. Aires de Sousa, D. A. R. S. Latino, A. Deluca, D. Horvath, V. Rietsch, A. Varnek, “Expert System for Predicting Reaction Conditions: The Michael Reaction Case”, J. Chem. Inf. Model. 2015, 55, 239-250. Impact Factor: 3.657 (in 2015), 3.760 (in 2016). Citations: 6; 5.

18. F. Pereira, D. A. R. S. Latino, S. P. Gaudˆencio, ”QSAR-Assisted Virtual Screening of Lead- Like Molecules from Marine and Microbial Natural Sources for Antitumor and Antibiotic Drug Discovery”, Molecules 2015, 20, 4848-4873. Impact Factor: 2.465 (in 2015), 2.861 (in 2016). Citations: 2; 4.

19. D. A. R. S. Latino, F. Pereira, “Exploration of Quantitative Structure-Reactivity Relation- ships for the Estimation of Mayr Nucleophilicity”, Helv. Chim. Acta 2015, 98, 863-879. Impact Factor: 1.087 (in 2015), 1.071 (in 2016). Citations: 0; 0.

8 20. J. Wicker, T. Lorsbach, M. Gutlein,¨ E. Schmid, D. A. R. S. Latino, S. Kramer, K. Fenner, “enviPath - The Environmental Contaminant Biotransformation Pathway Resource”, Nu- cleic Acids Res. 2016, 44, D502-D508. Impact Factor: 10.162 (in 2016), 10.162 (in 2016). Citations: 10; 13.

21. F. Pereira, K. Xiao, D. A. R. S. Latino, C. Wu, Q. Zhang and J. Aires-de-Sousa, “Machine Learning Methods to Predict Density Functional Theory B3LYP Energies of HOMO and LUMO Orbitals”, J. Chem. Inf. Model. 2017, 57, 11-21. Impact Factor: 3.760 (in 2016), 3.760 (in 2016). Citations: 0; 2.

22. D. A. R. S. Latino, J. Wicker, M. Gutlein,¨ E. Schmid, S. Kramer, K. Fenner, “Eawag-Soil in enviPath: A new resource for exploring regulatory pesticide soil biodegradation pathways and half-life data”, Environ. Sci.: Processes Impacts, 2017, 19, 449-464. Impact Factor: 2.592 (in 2016), 2.592 (in 2016). Citations: 1; 1.

23. A. Soares, M. S. Estev˜ao,M. M. Marques, V. Kovalishyn, D. A. R. S. Latino, J. Aires- de-Sousa, J. Ramos, M. Viveiros, and F. Martins, ”Synthesis and Biological Evaluation of Hybrid 1,5- and 2,5-Disubstituted Indoles as Potentially New Antitubercular Agents” , Med. Chem. 2017, 13, 439-447. Impact Factor: 2.331 (in 2016), 2.331 (in 2016). Citations: 0; 0.

24. D. A. R. S. Latino, Q. Zhang and J. Aires-de-Sousa, “Machine Learning Methods to Predict Density Functional Theory B3LYP Bond Lenghts”, J. Chem. Inf. Model. to be submit- ted, 2017. Impact Factor: 3.760 (in 2016), 3.760 (in 2016). Citations: -.

6.1.4 Papers in National Scientific Periodicals with Referees

1. D. A. R. S. Latino, L. M. V. Pinheiro, F. F. M. Freitas, F. M. S. Silva Fernandes, A. R. T. Calado, “Prediction of Lipophilicity by Feed-Forward Neural Networks using Topological Descriptors”, Revista Portuguesa de Farm´acia, ISSN 0484 - 811 X, Volume LII (nº2), 2005.

2. G. Carrera, D. A. R. S. Latino, J. Aires-de-Sousa, ”Machine Learning of Chemical Reactivity from Databases of Organic Reactions”, Revista Portuguesa de Farm´acia, ISSN 0484 - 811 X, Volume LII (nº3), 2008, p´ag.14. (Meeting Abstract)

6.1.5 Other Publications with Referees

1. D. A. R. S. Latino, F. F. M. Freitas, F. M. S. S. Fernandes, “Prediction of Chemical Reactivity by Artificial Neural Networks”, Chemistry Preprint Server, 2003, 10, 34-47.

2. D. A. R. S. Latino, J. Aires-de-Sousa, ”Genome-scale classification of metabolic reactions without assignment of reaction centers”, Abstracts of Papers of the American Chemical Society, ISSN 0065-7727, 2006, 231, 78-CINF. (Meeting Abstract)

3. J. Aires-de-Sousa, D. A. R. S. Latino, “A chemoinformatics approach to the classification of enzymatic reactions”, Abstracts of Papers of the American Chemical Society, ISSN 0065- 7727, 2006, 23 2, 185-BIOL, pag. 707. (Meeting Abstract)

9 4. J. Aires-de-Sousa, S. Gupta, D. A. R. S. Latino, Q. Y. Zhang, “Classification of organic and bio-organic reactions with MOLMAP physicochemical descriptors”, Abstracts of Papers of the American Chemical Society, ISSN 0065-7727, 2006, 23 2, 104-CINF. (Meeting Abstract)

5. F. Pereira, D. A. R. S. Latino, S. P. Gaudˆencio, “A QSAR Approach for Virtual Screening of Lead-Like Molecules en Route to Antitumor and Antibiotic Drugs from Marine and Microbial Natural Products”, DOI: 10.3389/conf.FMARS.2014.02.00062 Conference: Front. Mar. Sci. IMMR | International Meeting on Marine Research, 2014.

6. D. A. R. S. Latino, “Redes Neuronais Artificiais em Qu´ımica”, WikiCiˆencias 2014, 5(07), 0810. (http://wikiciencias.casadasciencias.org/wiki/index.php/Redes Neuronais Artificiais)

7. J. Aires-de-Sousa, D. A. R. S. Latino, “Energies of the HOMO and LUMO Orbitals for 111275 Organic Molecules Calculated by DFT B3LYP / 6-31G*”, figshare, 2016, https://dx.doi.org/10.6084/m9.figshare.3384184.

6.2 Oral and Poster Communications

6.2.1 Oral Communications in Scientific Conferences

1. J. Aires-de-Sousa, D. A. R. S. Latino, “Genome - Scale Classification of Metabolic Reactions without Assignment of Reaction Centers”, 231st - ACS National Meeting & Exposition, CINF Symposium in Advances in Reaction Informatics, Atlanta, 2006.

2. D. A. R. S. Latino, F. F. M. Freitas, J. Aires-de-Sousa, F. M. S. Silva Fernandes, “Can Artificial Neural Networks Provide Accurate Potential Energy Surfaces for Molecular Dy- namics Simulations?”, EUCOCC6 - 6thEuropean Conference in , Tale, Slovakia, 2006.

3. Q.-Y. Zhang, D. A. R. S. Latino, J. Aires-de-Sousa, “Molecular Maps of Atom-level Prop- erties (MOLMAPs) Calculated from Empirical or Semi-Empirical Methods”, EUCOCC6 - 6thEuropean Conference in Computational Chemistry, Tale, Slovakia, 2006.

4. J. Aires-de-Sousa, S. Gupta, D. A. R. S. Latino, Q.-Y. Zhang, “Classification of Organic and Bio-Organic Reactions with MOLMAP Physicochemical Descriptors”, 232nd - ACS National Meeting & Exposition, CINF Division, San Francisco, 2006.

5. J. Aires-de-Sousa, D. A. R. S. Latino, “From the Classification of Chemical Bonds to the Comparison of Reactomes: an Exercise in Chemoinformatics”, 2ndGerman Conference in Chemoinformatics, Goslar, Germany, 2006.

6. J. Aires-de-Sousa, D. A. R. S. Latino, ”Reactome Data Mining: a Chemoinformatics Explo- ration”, CIFARF 2007 - 6th International Congress of Pharmaceutical Sciences, Ribeir˜ao Preto, Brasil, 2007.

7. G. Carrera, D. A. R. S. Latino, J. Aires-de-Sousa, ”Machine Learning of Chemical Reactivity from Databases of Organic Reactions”, 1st National Meeting on Medicinal Chemistry, Porto, Portugal, 2008.

10 8. J. Aires-de-Sousa, X. Qu, D. A. R. S. Latino, R. P. Fartaria, F. Pereira, Q. Zhang, T. Zhao, “A QSPR Approach for Ultra-Fast Estimation of DFT-Calculated Molecular Properties”, VIII Colloquium Chemiometricum Mediterraneum, Bevagna, Italy, 2013.

9. F. Pereira, D. A. R. S. Latino, S. P. Gaudˆencio, “A QSAR Approach for Virtual Screening of Lead-Like Molecules en Route to Antitumor and Antibiotic Drugs from Marine and Microbial Natural Products”, International Meeting on Marine Research 2014, IMMR’14, Peniche, Portugal, 2014.

10. D. A. R. S. Latino and K. Fenner, “Reactome-Based Encoding of Microbial Communities and their Application to Contaminant Biotransformation Prediction”, ICCE 2015 - 15th EuCheMS International Conference on Chemistry and Environment, Leipzig, Germany, 2015.

6.2.2 Other Oral Communications

1. D. A. R. S. Latino, “Aplica¸c˜aode Redes Neuronais Artificiais `aQu´ımica”, Ciclo de Sem- in´arios “Qu´ımica `aSexta”, Dep. of Chemistry and Biochemistry, Faculty of Sciences, Uni- versity of Lisbon, 2002.

2. D. A. R. S. Latino, ”Classifica¸c˜aoAutom´atica de Reac¸c˜oes Qu´ımicas a partir de Espectros de 1H RMN”, Semin´arios de Qu´ımica Orgˆanica, Centro de Qu´ımica Fina e Biotecnologia, Faculty of Sciences and Technology, New University of Lisbon, 2005.

3. D. A. R. S. Latino and Jo˜aoAires-de-Sousa, ”Genome-Scale Classification of Enzymatic Reactions and Prediction of Chemical Reactivity with Automatic Learning Methods”, Sem- in´arios IMed.UL (Institute for Medicines and Pharmaceutical Sciences), Faculty of Phar- macy, University of Lisbon, 2008.

6.2.3 Posters in Scientific Conferences

1. D. A. R. S. Latino, F. M. S. S. Fernandes, F. F. M. Freitas, “Artificial Neural Networks: Pre- diction of Chemical Reactivity”, 6º Encontro Nacional de Qu´ımica-F´ısica, Lisbon, Portugal, 2003.

2. D. A. R. S. Latino, C. Borges, F. F. M. Freitas, F. M. S. S. Fernandes, M. A. A. Ferreira, “Study of Fragmentation Mechanisms of Isoflavones by Artificial Neural Networks”, XIX Encontro Nacional da Sociedade Portuguesa de Qu´ımica, Coimbra, Portugal, 2004.

3. D. A. R. S. Latino, C. Borges, F. F. M. Freitas, F. M. S. S. Fernandes, M. A. A. Ferreira, ”Proton Affinities of Isoflavones. Computational Study of Protonation Sites.”, EUCOCC5 - 5th European Conference on Computational Chemistry, La Londe les Maures, France, 2004.

4. D. A. R. S. Latino, C. Borges, F. F. M. Freitas, F. M. S. S. Fernandes, M. A. A. Ferreira, “Analysis of Antioxidant Activity of Isoflavones by Computational Methods”, Euroanalysis XIII - European Conference on Analytical Chemistry, Salamanca, Espanha, 2004.

11 5. D. A. R. S. Latino, L. M. V. Pinheiro, F. F. M. Freitas, F. M. S. S. Fernandes, A. R. T. Calado, “Prediction of Lipophilicity by Feed-Forward Neural Networks using Topologi- cal Descriptors”, 2nd Congress of the Pharmaceutical Sciences and 6th Portuguese-Spanish Congress on Controlled Release, Coimbra, Portugal, 2005.

6. D. A. R. S. Latino, F. F. M. Freitas, F. M. S. S. Fernandes, J. Aires-de-Sousa, “1H NMR - Based Classification of Photochemical Reactions”, 7th ICCS - 7th International Conference on Chemical Sructures, Noordwijkerhout, The Netherlands, 2005.

7. D. A. R. S. Latino, J. Aires-de-Sousa, F. F. M. Freitas, F. M. S. S. Fernandes, “Automatic Classification of Photochemical Reactions from 1H NMR Data”, 6º ENQO - 6º Encontro Nacional de Qu´ımica Orgˆanica , Braga, Portugal, 2005.

8. D. A. R. S. Latino, J. Aires-de-Sousa, “Genome-Scale Classification of Metabolic Reac- tions:a Chemoinformatics Approach”, Workshop Chemoinformatics in Europe: Research and Teaching, VVF Obernai, France, 2006.

9. D. A. R. S. Latino, J. Aires-de-Sousa, “Exploring the Reactome with Machine Learning Methods: Genome-Scale Mapping of Metabolic Reactions and Automatic Assignment of EC Numbers”, EUCOCC6 - 6thEuropean Conference in Computational Chemistry, Tale, Slovakia, 2006.

10. J. Aires-de-Sousa, D. A. R. S. Latino, “A Chemoinformatics Approach to the Classification of Enzymatic Reactions”, 232nd - ACS National Meeting & Exposition, Division of Biological Chemistry, San Francisco, 2006.

11. D. A. R. S. Latino, L. M. V. Pinheiro, F. F. M. Freitas, J. Aires-de Sousa, F. M. S. S. Fernandes, “Prediction of Antibacterial Activity of Diterpenes against MRSA with Machine Learning Methods”, Medicinal Chemistry in the 21st Century, Lisbon, Portugal, 2006.

12. D. A. R. S. Latino, J. Aires-de-Sousa,“Self-Organizing Maps in the Classification of Metabolic Reactions: the First Three Digits of the EC Number”, 2ndGerman Conference in Chemoin- formatics, Goslar, Germany, 2006.

13. D. A. R. S. Latino, J. Aires-de-Sousa, “Chemical Reactions in Bioinformatics: Encoding the Catalytic Function of Enzymes”, XX Encontro Nacional da Sociedade Portuguesa de Qu´ımica, Costa da Caparica, Portugal, 2006.

14. D. A. R. S. Latino, R. P. S. Fartaria, F. F. M. Freitas, J. Aires-de-Sousa, F. M. S. S. Fernandes, ”Approach of Potential Energy Surfaces by Neural Networks”, 8º ENQF - 8º Encontro Nacional de Qu´ımica-F´ısica, Luso, Portugal, 2007.

15. C. Ventura, J. Manso, D. Latino, F. Martins, “Comparative QSAR Analysis of Anti- Tubercular Compounds using Artificial Neural Networks and Multiple Linear Regression”, ESOR XI - 11th European Symposium on Organic Chemistry, Faro, Portugal, 2007.

16. D. A. R. S. Latino, J. Aires-de-Sousa, ”Transforming Organic Reactions into Numbers: Application to Genome-Scale Mapping of Enzymatic Reactions”, 7º ENQO - 7º Encontro Nacional de Qu´ımica Orgˆanica , Lisbon, Portugal, 2007.

12 17. D. A. R. S. Latino, J. Aires-de-Sousa, ”Linking Chemical and Genomic Information: Chemoin- formatics Classification of Enzyme Function”, 15th Annual International Conference on Intelligent Systems for Molecular Biology (ISMB) & 6th European Conference on Compu- tational Biology (ECCB), Vienna, Austria, 2007.

18. Y. Binev, J. Aires-de-Sousa, D. A. R. S. Latino, ”Neural Network Prediction of Full 1H NMR Spectra from Molecular Structure”, Conferentia Chemometrica, Budapest, 2007.

19. J. Aires-de-Sousa, D. A. R. S. Latino, “Genome-Scale Classification of Enzymatic Reactions and Pathways with Self-Organizing Maps”, 235th - ACS National Meeting & Exposition, CINF Division, New Orleans, 2008.

20. D. A. R. S. Latino, R. P. S. Fartaria, F. F. M. Freitas, J. Aires-de-Sousa, F. M. S. S. Fer- nandes, “Approach to Potential Energy Surfaces of Ethanol / Au (111) Interfaces by Neu- ral Networks”, EUCOCC7 - 7thEuropean Conference in Computational Chemistry, Venice, Italy, 2008.

21. D. A. R. S. Latino, L. M. V. Pinheiro, F. Sim˜oes, F. F. M. Freitas, F. M. S. S. Fernan- des, “Modelling Diterpenes Antibacterial Activity against MRSA using Automatic Learning Methods”, 3rd EuCheMS Chemistry Congress, Nurnberg, Germany, 2010.

22. C. Ventura, D. A. R. S. Latino, R. Leit˜ao,F. Martins, “Performance of Different QSAR Methodologies in the Modeling of Antitubercular Activity: Multiple Linear Regressions and Neural Networks”, 19th EuroQSAR, Vienna, Austria, 2012.

23. P. A. S. Salgueiro, C. Borges, J. Aires-de-Sousa, D. A. R. S. Latino, R. P. Fartaria, R. J. N. B. Silva, “Validation of the Conservation of Fire Debris Samples for the Identification of Ig- nitable Liquid Residues”, The Eurachem Workshop on Quality Assurance of Measurements from Field to Laboratory, Espoo, Finland, 2013.

24. P. A. S. Salgueiro, C. M. F. S. Borges, J. Aires-de-Sousa, D. A. R. S. Latino, R. P. Fartaria, R. J. N. B. Silva, “Evaluation of the Uncertainty of Arson Detection by Mass Spectrometry Assisted with Machine Learning Tools”, 2nd Middle Eastern and Mediterranean Sea Region Contries - Massa 2013, Mass Spectrometry Workshop, Siena, Italy, 2013.

25. J. Aires-de-Sousa, P. A. S. Salgueiro, D. A. R. S. Latino, R. P. Fartaria, R. J. N. B. Silva, C. M. F. S. Borges, “Machine Learning Classification of Neat and Burnt Ignitable Liquids for Arson Detection”, VIII Colloquium Chemiometricum Mediterraneum, Bevagna, Italy, 2013.

26. F. Pereira, D. A. R. S. Latino, S. P. Gaudˆencio, “In Silico Screening of Lead-Like Molecules en Route to Antitumor and Antibiotic Drugs from Marine and Microbial Natural Prod- ucts using Empirical and Semi-Empirical Quantum-Chemical Descritors”, 11th International Workshop on Computational Systems Biology, WCSB 2014, Costa de Caparica, Portugal, 2014.

27. F. Martins, S. Santos, C. Ventura, R. Elvas-Leit˜ao,L. Santos, S. Vitorino, M. Reis, V. Miranda, H. F. Correia, J. Aires-de-Sousa, V. Kovalishyn , D. A. R. S. Latino, J. Ramos,

13 M. Viveiros, “A Successful QSAR Strategy for the Development of New Antitubercular Compounds, 20th EuroQSAR, St. Petersburg, Russia, 2014.

28. P. A. S. Salgueiro, C. Borges, J. Aires-de-Sousa, D. A. R. S. Latino, R. P. Fartaria, R. J. N. B. Silva, “Chemometric Arson Detection with Known Uncertainty”, Pittcon 2015 - Pittcon Annual Premier Conference and Exposition on Laboratory Science, New Orleans, USA, 2015.

29. J. Wicker, T. Lorsbach, M. Gutlein,¨ E. Schmid, D. A. R. S. Latino, S. Kramer and K. Fenner, “enviPath – The environmental contaminant biotransformation pathway resource”, SETAC (Society of Environmental Toxicology and Chemistry) Europe 26th Annual Meeting, Nantes, France, 2016.

30. C. Mansfeldt, S. Achermann, K. Udert, M. Kipf, D. Latino, A. Joss, and K. Fenner, “Linking the bacterial community succession in an aerobic reactor treating urine to the time-varying biotransformation of micropollutants”, ISME 2016 - 16th International Symposium on Mi- crobial Ecology, Montreal, Canada, 2016.

31. A. Lai, D. Latino, K. Fenner, “Using EFSA Regulatory Data to Explore Pesticide Biodegra- dation Half-life Variability”, SETAC (Society of Environmental Toxicology and Chemistry) Europe 27th Annual Meeting, Brussels, Belgium, 2017.

32. D. A. R. S. Latino, J. Wicker, A. Lai, M. Gutlein,¨ E. Schmid, S. Kramer and K. Fenner, “Eawag-Soil: a new resource for exploring regulatory pesticide soil biodegradation pathways and half-life data”, Pesticide Behaviour in Soils, Water and Air, York, UK, 2017 (submitted)

6.3 Participation in Projects

1. Project “CH-2007-0990 - Development and Use of new Chemoinformatics approaches to integrate Chemical Reactivity data in the area of Skin Sensitisation.” SEAC (Safety & Environmental Assurance Centre), UNILEVER UK / Faculty of Sciences and Technology, New University of Lisbon. Participation as Post-Doc Researcher (2008 - 2009)

2. Project “BPD/REQUIMTE/JAS/01/2010 - Exploration of new chemical bond descriptors for the prediction and automatic classification of reactivity.” REQUIMTE, Faculty of Sciences and Technology, New University of Lisbon. Participation as Post-Doc Researcher (2010)

3. Project“PTDC/QUI/67933/2006 - From Design to Synthesis of New Anti-Tubercular Agents.” REQUIMTE, Faculty of Sciences and Technology, New University of Lisbon. Participation as Post-Doc Researcher (2011)

4. Project “SFRH/BPD/63192/2009 - Chemoinformatics approaches for the prediction of mul- tiple toxicological endpoints and risk assessment of chemicals.” REQUIMTE, Faculty of Sciences and Technology, New University of Lisbon. Participation as Post-Doc Researcher (2011 - 2014)

14 5. Project “PROGRAMA PESSOA 2013/2014: Proc. 441.00 - Automatic Processing and Classification of Organic and Metabolic Reactions” Coopera¸c˜aoTransnacional - Portugal / Fran¸ca, Funda¸c˜aopara a Ciˆencia e Tecnologia Participation as Researcher (2013 - 2014)

6. Project “PROduCTS - Predicting environment-specific biotransformation of chemical con- taminants” European Research Council (ERC) Participation as Researcher (since 2014)

6.4 Honours and Awards

ˆ 1st Place in Olympiads of Mathematics, (7th and 8th year) Escola Secund´aria de Mira Sintra, Mira-Sintra, 1992.

ˆ PhD Scholarship FCT (Portuguese National Science Foundation), 2004.

ˆ Gasteiger Award (Award for the two best posters) Workshop Chemoinformatics in Europe: Research and Teaching, Obernai, France, 2006.

ˆ Award for the best Poster of EUCOCC7 in Poster Session II - Advanced Applications EUCOCC7 - 7th European Conference in Computational Chemistry, Venice, Italy, 2008.

ˆ Post-doc Fellowship FCT (Portuguese National Science Foundation), 2009.

ˆ SAS Institute Award for Academic Excellence Incentive - Best Student in the Course of Data Mining I in Post-Graduation/Master degrees Nova IMS, 2013-2014.

6.5 Collaborations with other Groups

1. Environmental and Biological Mass Spectrometry Group, CQB (Centro de Qu´ımica e Bio- qu´ımica), Prof. Carlos Borges, Faculty of Sciences, University of Lisbon (2001 - 2005).

2. Molecular Simulation Group, CCMM (Centro de Ciˆencias Moleculares e Materiais), Prof. Fernando Fernandes and Prof. Filomena Freitas, Faculty of Sciences, University of Lisbon (Since 2001).

3. Biophysical Chemistry Group, CCF (Centro de Ciˆencias Farmacˆeuticas), Prof. Ant´onio R. T. Calado and Prof. Lidia M. V. Pinheiro, Faculty of Pharmacy, University of Lisbon (2004 - 2010).

4. Structure and Reactivity Group, CQB (Centro de Qu´ımica e Bioqu´ımica), Prof. Filomena Martins and Prof. Cristina Ventura, Faculty of Sciences, University of Lisbon (Since 2005).

5. Organic Chemistry Group, REQUIMTE, Prof. Maria Manuel Marques, Faculty of Sciences and Technology, New University of Lisbon, (2010-2015).

15 6.6 Collaborations with Industry

ˆ SEAC (Safety & Environmental Assurance Centre), Unilever UK (2008/2009)

ˆ Molecular Networks GmbH (2008/2009)

7 Teaching Activity

7.1 Students Supervision

7.1.1 Master Thesis

1. Name: Adelene Lai Master: Biogeochemistry and Pollutant Dynamics Title: “Modelling of Pesticide Degradation in Aerobic Soil.” Local: Eawag, Department of Environmental Chemistry and ETH, Department of Envi- ronmental Sciences. Supervisor: Prof. Kathrin Fenner. Co-Supervisors: Dr. Diogo A. R. S. Latino. Classification: Ongoing.

7.1.2 Research Dissertation for Graduation

1. Name: Jorge M. C. S. Silva Licenciatura: Biochemistry Title: “Chemoinformatics Methods for the Prediction of Reactivity Parameters from the Molecular Structure.” Dep. of Chemistry, Faculty of Sciences and Technology, New University of Lisbon, Chemoin- formatics Group, 2011. Supervisor: Prof. Jo˜aoAires-de-Sousa. Co-Supervisors: Dr. Diogo A. R. S. Latino and Dra. Florbela Pereira. Classification: 16 out of 20.

2. Name: Tiago Campos Licenciatura: Applied Chemistry Title: “Development of Chemoinformatics Approaches for the Prediction of Chemical Re- activity.” Local: Dep. of Chemistry, Faculty of Sciences and Technology, New University of Lisbon, Chemoinformatics Group, 2012. Supervisor: Prof. Jo˜aoAires-de-Sousa. Co-Supervisors: Dr. Diogo A. R. S. Latino. Classification: 15 out of 20.

3. Name: Benjamin Wolfer Bachelor: Environmental Sciences Title: “Finding Rules for Biotransformation Pathway Prediction.”

16 Local: Eawag, Department of Environmental Chemistry and ETH, Department of Envi- ronmental Sciences, 2016. Supervisor: Prof. Kathrin Fenner. Co-Supervisors: Dr. Diogo A. R. S. Latino. Classification: Approved.

7.2 Undergraduate Courses

7.2.1 In Dep. of Chemistry and Biochemistry, Faculty of Sciences, University of Lisbon

1. “Initiation to Research in the area of Computational Chemistry”, Graduation in Chemistry Supervisor: Prof. Filomena F. M. Freitas, in 2001/2002

2. “Computational Chemistry II”, Graduation in Chemistry Supervisor: Prof. Fernando M. S. S. Fernandes, in 2003/2004

3. ”Computational Chemistry I”, Graduation in Chemistry Supervisor: Prof. Fernando M. S. S. Fernandes, in 2004/2005 and 2005/2006

7.2.2 In Dep. of Chemistry, Faculty of Sciences and Technology, New University of Lisbon

1. ”Chemistry I”, Graduation in “Eng. de Gest˜aoIndustrial” and “Eng. Mecˆanica” Supervisor: Prof. Henrique Guedes. in 2007/2008.

2. ”Computational Chemistry”, Graduation in Applied Chemistry Supervisor: Prof. Jo˜aoAires-de-Sousa. in 2007/2008.

3. “Chemistry I”, Graduation in ”Eng. de Civil” and ”Eng. Materiais” Supervisor: Prof. Jo˜aoAires-de-Sousa. in 2008/2009.

4. ”Computational Chemistry”, Graduation in Applied Chemistry and Biochemistry Supervisor: Prof. Jo˜aoAires-de-Sousa. in 2009/2010.

7.3 Postgraduate Courses

7.3.1 In Dep. of Chemistry and Biochemistry, Faculty of Sciences, University of Lisbon

1. “Numerical Methods”, Post-Graduation in Applied Electrochemistry Supervisor: Prof. Fernando M. S. S. Fernandes, in 2003/2004.

2. “Molecular Modeling - Artificial Neural Networks in QSAR”, Post-Graduation in Biomedical Inorganic Chemistry Supervisor: Prof. Fernando M. S. S. Fernandes, in 2004/2005 and 2005/2006.

3. “Informatics Applications in Chemical Analysis”, Post-Graduation in Applied Analytical Chemistry Supervisor: Prof. Filomena Duarte, in 2006/2007.

17 4. “Molecular Modeling - Chemoinformatics”, Post-Graduation in Biomedical Inorganic Chem- istry Supervisor: Prof. Fernando M. S. S. Fernandes, in 2006/2007 and 2009/2010.

5. ”Application of SARs and QSARs in Drug Design”, Post-Graduation in Chemistry, Health and Nutrition Supervisor: Prof. Filomena Martins, in 2007/2008 and 2010/2011.

6. “Neural Networks and Chemometrics”, Post-Graduation in Chemistry Supervisor: Prof. Filomena Cam˜oes,in 2010/2011.

7.3.2 In Dep. of Chemistry, Faculty of Sciences and Technology, New University of Lisbon

1. ”Applied Computational Chemistry”, Post-Graduation in Biorganic Chemistry Supervisor : Prof. Jo˜aoAires de Sousa, in 2008/2009, 2009-2010.

7.4 Other Courses

7.4.1 In Faculty of Pharmacy, University of Lisbon

1. “Application of Neural Networks in Chemistry”, Formation Course in “Molecular Modeling in Pharmaceutical Sciences”, 15-17 February, 2007, FFUL. Supervisor: Prof. Rita Guedes.

8 Participation in Organizing Committees of Scientific Conferences

1. Organizing Committee of the “6º Encontro Nacional de Qu´ımica-F´ısica” Sociedade Portuguesa de Qu´ımica, Lisbon, Portugal, 2003.

2. Colaboration in the Organization of the “7º Encontro Nacional de Qu´ımica Orgˆanica” Sociedade Portuguesa de Qu´ımica, Lisbon, Portugal, 2007.

9 Chemoinformatics Skills

9.1 Software (scientific research)

9.1.1 Molecular descriptors calculation

ˆ PETRA (Parameter Estimation for the Treatment of Reactivity Applications) - Calculation of physico-chemical properties of molecules.

ˆ ADRIANA.Code - Calculation of structural molecular descriptors.

ˆ CXCALC - tool from JCHEM software package.

ˆ DRAGON

ˆ CDK (Chemistry Development Kit)

18 9.1.2 Optimization of molecular structures

ˆ CORINA (COoRdINAtes)

ˆ MOPAC (Molecular Orbital PACkage)

ˆ GAMESS (General Atomic and Molecular Electronic Structure System)

ˆ Gaussian (structure calculation software)

9.1.3 machine learning and/ or statistical methods

ˆ JATOON (JAva TOOls for Neural networks) - Implementation of Neural Networks:

– Kohonen Self-Organizing Maps (SOMs) – Counter-Propagation Neural Networks (CPNNs) – Feed-Forward Neural Networks (FFNNs)

ˆ R software environment for statistical computing and graphics - namely the packages to implement:

– Random Forests – Regression Trees – Decision Trees – clustering – non-linear minimization

ˆ AsNN (Associative Neural Networks software):

– Feed-Forward Neural Networks (FFNNs) – Ensembles of Feed-Forward Neural Networks (EnsFFNNs) – Associative Neural Networks

ˆ JavaNNS (Java Neural Network Simulator)

ˆ SONNIA (Self-Organizing Neural Network for Information Analysis)

ˆ WEKA (collection of machine learning algorithms for data mining tasks) - using of several tools for data pre-processing, classification, regression, clustering, association, and visual- ization, for example:

– Multi-Linear Regressions – Decision Trees – Regression Trees – Modelling Trees – Random Forests

19 – Support Vector Machines – Feed-Forward Neural Networks – Techniques for selection of descriptors

9.1.4 Others

ˆ Molekel, , PovRay, MolMol - Experience in 3D representation of molecular structures and generation of input files.

ˆ SPINUS (Structure - based Predictions In NUclear magnetic Spectroscopy) - Prediction of 1H NMR spectra.

10 Languages

Languages Comprehension Conversation Writing Oral Reading Oral interaction Oral Production Portuguese Excelent Excelent Excelent Excelent Excelent English Good Excelent Good Good Good

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