Bioinformatics of infectious and chronic diseases at the Center for Technological Development in Health of Fiocruz
DOI:
https://doi.org/10.5753/jidm.2024.2625Keywords:
Information retrieval, Data Mining and Integration, System ModelingAbstract
One of the bioinformatics purposes is data mining and integration to solve fundamental scientific challenges. We have been investigating biological systems including viruses, bacteria, fungi, protozoans, plants, insects, and animals with such concern. Gradually, we moved from basic questions on genome organization to application in infectious and chronic diseases by integrating interactome and RNA-seq data to modeling techniques such as Flux Balance Analysis, structural modeling, Boolean modeling, system dynamics, and computation biology in a system biology perspective. At the moment, we focus on the rational therapy of cancer assisted by RNA sequencing, network modeling, and structural modeling.
Downloads
References
Adel, A. and Carels, N. (2023). Plant tolerance to drought stress with emphasis on wheat. Plants, 12(11):2170.
Agrios, G. N. (2004). Plant Pathology. Elsevier.
Albert, R., Jeong, H., and Barabási, A.-L. (2000). Error and attack tolerance of complex networks. Nature, 406(6794):378–382.
Antunes, L. C. M., Han, J., Pan, J., Moreira, C. J. C., Azambuja, P., Borchers, C. H., and Carels, N. (2013). Metabolic signatures of triatomine Vectors of Trypanosoma cruzi unveiled by metabolomics. Plos One, 8:e77283–12.
Barabási, A.-L. (2016). Network Science. CambridgeUniversityPress.
Barbosa-Silva, A., Magalhães, M., da Silva, G. F., da Silva, F. A. B., Carneiro, F. R. G., and Carels, N. (2022). A data science approach for the identification of molecular signatures of aggressive cancers. Cancers, 14(9):2325.
Bernardi, G. (2021). The ”Genomic Code”: DNA pervasively moulds chromatin structures leaving no room for ”Junk”. Life, 11(4):342.
Burgess, L. W. and Bryden, W. L. (2012). Fusarium: a ubiquitous fungus of global significance. Microbiol Australia, 33(1):22.
Carels, N. (2005a). Recent Research Developments in Plant Science, chapter The genome organization of angiosperms, pages 129–194. Research Signpost.
Carels, N. (2005b). The maize gene space is compositionally compartimentalized. FEBS Letters, 579(18):3867–3871.
Carels, N. and Bernardi, G. (2000). Two classes of genes in plants. Genetics, 154:1819–1825.
Carels, N. and Frias, D. (2013a). A statistical method without training step for the classification of coding Frame in transcriptome sequences. Bioinf Biol Insights, 7:35–54.
Carels, N. and Frias, D. (2013b). BIOMAT 2012, chapter The contribution of stop codon frequency and purine bias to the classification of coding sequences, pages 301–322. World Scientific.
Carels, N., Gumiel, M., da Mota, F. F., Moreira, C. J., and Azambuja, P. (2017). A metagenomic analysis of bacterial microbiota in the digestive tract of triatomines. Bioinf Biol Insights, 11:117793221773342.
Carels, N., Hatey, P., Jabbari, K., and Bernardi, G. (1998). Compositional properties of homologous coding sequences from plants. J Mol Evol, 46:45–53.
Carels, N. and Ponce de Leon, M. (2015). An interpretation of the ancestral codon from Miller’s amino acids and nucleotide correlations in modern coding sequences. Bioinf Biol Insights, 9:37–47.
Carels, N., Tilli, T., and Tuszynski, J. A. (2015). A computational strategy to select optimized protein targets for drug development toward the control of cancer diseases. Plos One, 10:e0115054–16.
Carels, N., Vidal, R., and Frías, D. (2009). Universal features for the classification of coding and non-coding DNA sequences. Bioinf Biol Insights, 3:37–49.
Catharina, L. and Carels, N. (2018). Specific enzyme functionalities of Fusarium oxysporum compared to host plants. 676:219–226.
Catharina, L., Lima, C. R., Franca, A., Guimarães, A. C. R., Alves-Ferreira, M., Tuffery, P., Derreumaux, P., and Carels, N. (2017). A computational methodology to overcome the challenges associated with the search for specific enzyme targets to develop drugs against Leishmania major. Bioinf Biol Insights, 11:1177932217712471.
Catharina, L. C. (2017). Busca de alvos proteicos para desenvolvimento de inibidores enziḿticos em sistemas hospedeiros-parasitos. PhD thesis, Fiocruz, Rio de Janeiro, Brazil.
Conforte, A. J., Alves, L., Coelho, F. C., Carels, N., and da Silva, F. A. B. (2020). Modeling basins of attraction for breast cancer using Hopfield networks. Front Genetics, 11:314–317.
Conforte, A. J., Tuszynski, J. A., da Silva, F. A. B., and Carels, N. (2019). Signaling complexity measured by Shannon entropy and its application in personalized medicine. Front Genetics, 10:1–14.
Costantini, M., Clay, O., Auletta, F., and Bernardi, G. (2006). An isochore map of human chromosomes. Genome Res, 16(4):536–541.
da Mota, F. F., Marinho, L. P., Moreira, C. J., Lima, M. M., Mello, C. B., Garcia, E. S., Carels, N., and Azambuja, P. (2012). Cultivation-independent methods reveal differences among bacterial gut microbiota in triatomine vectors of Chagas disease. PLos Negl Trop Dis, 6(5):e1631.
D’Argenio, V. (2018). The high-throughput analyses era: Are we ready for the data struggle? High Throughput, 7(1):8.
de Araújo, R. F. S., Carels, N., de Melo, P. R. S., and FRIAS, D. (2007). Investigation of polymorphisms in the genome of Dengue virus. RECIIS, 1:316–320.
D’Onofrio, G., Jabbari, K., Musto, H., and Bernardi, G. (1999). The correlation of protein hydropathy with the base composition of coding sequences. Gene, 238(1):3–14.
Fintelman-Rodrigues, N., Sacramento, C. Q., Lima, R. C., Souza da Silva, F., Ferreira, A. C., Mattos, M., de Freitas, C. S., Cardoso Soares, V., da Silva, G. D. S., Temerozo, J. R., Miranda, M. D., Matos, A. R., Bozza, F. A., Carels, N., Alves, C. R., Siqueira, M. M., Bozza, P. T., and Souza, T. M. L. (2020). Atazanavir, alone or in combination with ritonavir, inhibits SARS-CoV-2 replication and proinflammatory cytokine production. Antimicrob Agents Chemother, 64:e00825–20.
Garcia, D., Carels, N., Koop, D. M., de Souza, L. A., Andrade, J. S., Pujade-Renaud, V., Mattos, C. R. R., and Cascardo, J. C. M. (2011). EST profiling of resistant and susceptible Hevea infected by Microcyclus ulei. Physiol Mol Plant Pathol, 76:126–136.
Gauthier, J., Vincent, A. T., Charette, S. J., and Derome, N. (2019). A brief history of bioinformatics. Brief Bioinform, 20(6):1981–1996.
Gesteira, A. S., Micheli, F., Carels, N., Silva, A. C. D., Gramacho, K. P., SCHUSTER, I., Macedo, J. N., Pereira, G. A. G., and Cascardo, J. C. M. (2007). Comparative analysis of expressed genes from cacao meristems infected by Moniliophthora perniciosa. Ann Bot, 100:129–140.
Gomes, K. A., Almeida, T., Gesteira, A., Lobo, I. P., Guimarães, A. C. R., de Miranda, A. B., Sluys, M.-A. V., da Cruz, R. S., Cascardo, J. C. M., and Carels, N. (2010). ESTs from seeds to assist the selective breeding of Jatropha curcas L. for oil and active compounds. Genom Insights, 3:29–56.
Gomes, M. R., Guimarães, A. C. R., and de Miranda, A. B. (2011). Specific and nonhomologous isofunctional enzymes of the genetic information processing pathways as potential therapeutical targets for Tritryps. Enzyme Res, 2011:1–8.
Grochowski, K., Breiter, M., and Nowak, R. (2019). Introduction to Data Science and Machine Learning, chapter Serialization in Object-Oriented Programming languages, pages 873–891. InTech.
Gumiel, M., da Mota, F. F., Rizzo, V. S., Sarquis, O., de Castro, D. P., Lima, M. M., Garcia, E. S., Carels, N., and Azambuja, P. (2015). Characterization of the microbiota in the guts of Triatoma brasiliensis and Triatoma pseudo-maculata infected by Trypanosoma cruzi in natural conditions using culture independent methods. Parasit Vectors, 8:245.
Gumiel, M., de Mattos, D. P., Vieira, C. S., Moraes, C. S., Moreira, C. J. C., Gonzalez, M. S., Teixeira-Ferreira, A., Waghabi, M., Azambuja, P., and Carels, N. (2020). Proteome of the triatomine digestive tract: From catalytic to immune pathways; focusing on annexin expression. Front Mol Biosciences, 7:1–23.
Huang, S., Ernberg, I., and Kauffman, S. (2009). Cancer attractors: A systems view of tumors from a gene network dynamics and developmental perspective. Semin Cell Dev Biol, 20:869–876.
Irwin, J. J., Sterling, T., Mysinger, M. M., Bolstad, E. S., and Coleman, R. G. (2012). ZINC: a free tool to discover chemistry for biology. J Chem Inf Model, 52(7):1757–1768.
Kanehisa, M. and Goto, D. (2000). KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res, 28(1):27–30.
Kindler, E. and Krivy, I. (2011). Object-Oriented Simulation of systems with sophisticated control. Int J Gen Syst, 40(3):313–343.
Lechuga, G. C., Souza-Silva, F., Sacramento, C. Q., Trugilho, M. R. O., Valente, R. H., Napoleão-Pego, P., Dias, S. S. G., Fintelman-Rodrigues, N., Temerozo, J. R., Carels, N., Alves, C. R., Pereira, M. C. S., Provance, D. W. J., Souza, T. M. L., and De Simone, S. G. (2021). SARS-CoV-2 proteins bind to hemoglobin and its metabolites. Int J Mol Sci, 22(16):9035.
Lima, C. R., Carels, N., Guimarães, A. C. R., Tuffery, P., and Derreumaux, P. (2016). In silico structural characterization of protein targets for drug development against Trypanosoma cruzi. J Mol Model, 22:244.
Lima, L. S., Gramacho, K., Pires, J. L., Clément, D., Lopes, U. V., Carels, N., Gesteira, A., Gaiotto, F. A., Cascardo, J. C. M., and Micheli, F. (2010). Development, characterization, validation, and mapping of SSRs derived from Theobroma cacao L. - Moniliophthora perniciosa interaction ESTs. Tree Genet Genomes, 6:663–676.
Motta, S. and Pappalardo, F. (2013). Mathematical modeling of biological systems. Brief Bioinformatics, 14(4):411–422.
NRCCFICB (2005). Catalyzing Inquiry at the Interface of Computing and Biology. NationalAcademiesPress.
Orchard, S., Ammari, M., Aranda, B., Breuza, L., Briganti, L., Broackes-Carter, F., Campbell, N. H., Chavali, G., Chen, C., del Toro, N., Duesbury, M., Dumousseau, M., Galeota, E., Hinz, U., Iannuccelli, M., Jagannathan, S., Jimenez, R., Khadake, J., Lagreid, A., Licata, L., Lovering, R. C., Meldal, B., Melidoni, A. N., Milagros, M., Peluso, D., Perfetto, L., Porras, P., Raghunath, A., Ricard-Blum, S., Roechert, B., Stutz, A., Tognolli, M., van Roey, K., Cesareni, G., and Hermjakob, H. (2014). The MIntAct project–IntAct as a common curation platform for 11 molecular interaction databases. Nucleic Acids Res, 42:D358–D363.
Otto, T. D., Guimarães, A. C., Degrave, W. M., and de Miranda, A. B. (2008). AnEnPi: identification and annotation of analogous enzymes. BMC Bioinformatics, 9:544.
Pires, J. G., da Silva, G. F., Weyssow, T., Conforte, A. J., Pagnoncelli, D., da Silva, F. A. B., and Carels, N. (2021). Galaxy and MEAN Stack to create a user-friendly workflow for the rational optimization of cancer chemotherapy. Front Genetics, 12:155–181.
Ponce de Leon, M., de Miranda, A. B., Alvarez-Valin, F., and Carels, N. (2014). The purine bias of coding sequences is determined by physicochemical constraints on proteins. Bioinf Biol Insights, 8:93–108.
Sgariglia, D., Conforte, A. J., Pedreira, C. E., Vidal, C. L. A., Gonçalves, C. F. R., Carels, N., and Silva, F. A. B. (2021). Data-driven modeling of breast cancer tumors using Boolean networks. Front Big Data, 4:1–13.
Sgariglia, D., Gonçalves, C. F. R., de Carvalho, L., Pedreira, C., Carels, N., and Silva, F. A. B. (2023). Optimizing therapeutic targets for breast cancer using Boolean network models. bioRxiv, doi:10.1101/2023.05.10.540187.
Shannon, C. E. A. (1948). A mathematical theory of communication. Bell Syst Tech J, 27:379–423.
Takahashi, M., Kryukov, K., and Saitou, N. (2009). Estimation of bacterial species phylogeny through oligonucleotide frequency distances. Genomics, 93(6):525–533.
The Gene Ontology Consortium (2008). The Gene Ontology project in 2008. Nucleic Acids Res, 36:D440–D444.
Tilli, T. M., Carels, N., Tuszynski, J. A., and Pasdar, M. (2016). Validation of a network-based strategy for the optimization of combinatorial target selection in breast cancer therapy: siRNA knockdown of network targets in MDA-MB-231 cells as an in vitro model for inhibition of tumor development. OncoTarget, 7:63189–63203.
Vieira, M., Gonçalves, C. F. R., Côrtese, A., Carels, N., and Silva, F. A. B. (2023). Statistical characterization of the dynamics of Glioblastoma Multiforme subtypes through parameters estimation of the epigenetic landscape. bioRxiv, doi:10.1101/2023.04.25.538198.
Wishart, D. S., Feunang, Y. D., Guo, A. C., Lo, E. J., Marcu, A., Grant, J. R., Sajed, T., Johnson, D., Li, C., Sayeeda, Z., Assempour, N., Iynkkaran, I., Liu, Y., Maciejewski, A., Gale, N., Wilson, A., Chin, L., R., Cummings, Le, D., Pon, A., Knox, C., and Wilson, M. (2017). DrugBank 5.0: a major update to the DrugBank database for 2018. Nucleic Acids Res, 46(D1):D1074–D1082.
Wishart, D. S., Tzur, D., Knox, C., Eisner, R., Guo, A. C., Young, N., Cheng, D., Jewell, K., Arndt, D., Sawhney, S., Fung, C., Nikolai, L., Lewis, M., Coutouly, M. A., Forsythe, I., Tang, P., Shrivastava, S., Jeroncic, K., Stothard, P., Amegbey, G., Block, D., Hau, D. D., Wagner, J., Miniaci, J., Clements, M., Gebremedhin, M., Guo, N., Zhang, Y., Duggan, G. E., Macinnis, G. D., Weljie, A. M., Dowlatabadi, R., Bamforth, F., Clive, D., Greiner, R., Li, L., Marrie, T., Sykes, B. D., Vogel, H. J., and Querengesser, L. (2007). HMDB: the Human Metabolome Database. Nucleic Acids Res, 35:D521–D526.
Zhang, Y., Yang, H., Turra, D., Zhou, S., Ayhan, D. H., DeIulio, G. A., Guo, L., Broz, K., Wiederhold, N., Coleman, J. J., Donnell, K. O., Youngster, I., McAdam, A. J., Savinov, S., Shea, T., Young, S., Zeng, Q., Rep, M., Pearlman, E., Schwartz, D. C., Pietro, A. D., Kistler, H. C., and Ma, L.-J. (2020). The genome of opportunistic fungal pathogen Fusarium oxysporum carries a unique set of lineage-specific chromosomes. Commun Biol, 3:50.
