Background and activities
Marcio Luis Acencio received a Bachelor's degree in Biomedicine in 1998 from the Federal University of São Paulo (UNIFESP) in São Paulo, Brazil, a M.Sc. degree in Biotechnology in 2002 from the University in São Paulo (USP; http://www5.usp.br/english/?lang=en) in Sâo Paulo, Brazil, and a PhD degree in Genetics in 2011 from the School of Biosciences at the São Paulo State University (UNESP; http://www.unesp.br/international/), Botucatu, Brazil.
With a background in computational systems biology, machine learning, analysis of biological networks and bioinformatics focused on sequence and functional enrichment analyses, Marcio has been involved in large-scale projects such as the genome Sequence of the plant pathogen Xylella fastidiosa (http://www.ncbi.nlm.nih.gov/pubmed/10910347) and the The FAPESP / LICR human cancer genome project (http://www.ncbi.nlm.nih.gov/pubmed/14593198). Moreover, Marcio has also been involved in small scale projects regarding the (1) utilization of biological network features and machine learning to predict different aspects (essentiality [http://www.ncbi.nlm.nih.gov/pubmed/19758426], morbidity and druggability [http://www.ncbi.nlm.nih.gov/pubmed/21210975] and oncogenicity [http://www.ncbi.nlm.nih.gov/pubmed/24204854]) of genes, proteins and interactions, (2) construction of machine learning-based model to predict protein-protein interactions based solely in amino acid composition (http://www.ncbi.nlm.nih.gov/pubmed/23741499) and (3) functional enrichment analysis of plant (tobacco [http://www.ncbi.nlm.nih.gov/pubmed/26106890], coffee, eucalyptus) and cancer (chronic myeloid leukemia) transcriptomes.
Besides machine learning and functional enrichment analyses, Marcio has also been involved in biological knowledge management and data visualization. In 2012, he and other colleagues from UNESP made publicly available to the scientific community the Human Transcriptional Regulation Interactions Database (HTRIdb, http://www.lbbc.ibb.unesp.br/htri), a user-friendly and open-access database from which human experimentally validated interactions among transcription factors and their target genes can be easily extracted and used, for example, to construct transcriptional regulation interaction networks (http://www.ncbi.nlm.nih.gov/pubmed/22900683). In 2013, Marcio and colleagues from UNESP and the Federal University of Rio Grande do Sul (UFRGS, http://www.ufrgs.br/english/home) made publicly available a Cytoscape plugin, GALANT, that builds functional landscapes onto biological networks (http://www.ncbi.nlm.nih.gov/pubmed/23894138). By using GALANT, it is possible to project any type of numerical data onto a network to create a smoothed data map resembling the network layout (http://www.lbbc.ibb.unesp.br/galant/).
Currently, Marcio is a postdoctoral researcher working in the project "Crossover Research 2.0. Well constructed Knowledge Commons (CR2; https://www.ntnu.edu/crossover-research). The objective of CR2 is the creation of a broadly enabling Information and communications technology (ICT)-founded “Knowledge Commons” (KC) for the Life Sciences and the Health and Biotechnology sector based on the principles of the Responsible Research and Innovation (RRI). A KC is essential for storing and sharing comprehensive life science knowledge as well as for rationalizing and allowing interpretation of the wealth of biomedical findings and health data.
The principal investigator (PI) of CR2 is Rune Nydal (https://www.ntnu.no/ansatte/rune.nydal) and the co-PIs are Astrid Lægreid (http://www.ntnu.edu/employees/astrid.lagreid) and Martin Kuiper (http://www.ntnu.edu/employees/martin.kuiper). Besides Marcio, the postdoctors involved in CR2 are Ane Møller Gabrielsen (https://www.ntnu.no/ansatte/ane.gabrielsen) and Anamika Chatterjee, both working on in the RRI aspect of the project, and Steven Vercruysse (http://www.ntnu.edu/employees/steven.vercruysse), who is responsible for the development of new curation and annotation platforms, such as Scicura (http://scicura.org/).
The ICT-funded and RRI-based KC under development in the CR2 project will primarily store information about causal interactions among transcription factors (TFs) and their targets (TGs) and will serve as a kickoff for the Gene Regulation Consortium (GRECO, http://www.thegreco.org/), an emerging global initiative aimed at building a Gene Regulation Knowledge Commons that brings together major players from the global scientific community active in the domain of developing technologies and building resources for curating information and knowledge pertaining to gene regulation.
Marcio's role in this project is to curate, collect and annotate information about the causal interactions among about 500 mammalian TFs and their TGs from the biomedical literature. Moreover, he also has to manage and lead all the curation process, including the development of curation and annotation guidelines, establishment of a work plan and the preparation of the manuscript reporting the results of this process.
Scientific, academic and artistic work
A selection of recent journal publications, artistic productions, books, including book and report excerpts. See all publications in the database
- (2017) Impacts of the overexpression of a tomato translationally controlled tumor protein (TCTP) in tobacco revealed by phenotypic and transcriptomic analysis. Plant Cell Reports. vol. 36.
- (2016) Predicting essential genes and proteins based on machine learning and network topological features: a comprehensive review. Frontiers in Physiology. vol. 7:75.
- (2016) An ensemble framework for identifying essential proteins. BMC Bioinformatics. vol. 17 (1).
- (2015) Prediction of druggable proteins using machine learning and systems biology: a mini-review. Frontiers in Physiology. vol. 6.
- (2015) Transcriptome response signatures associated with the overexpression of a mitochondrial uncoupling protein (AtUCP1) in tobacco. PLoS ONE. vol. 10 (6).
- (2013) Prediction of oncogenic interactions and cancer-related signaling networks based on network topology. PLoS ONE. vol. 8 (10).
- (2013) The development of a universal in silico predictor of protein-protein interactions. PLoS ONE. vol. 8.
- (2013) GALANT: a Cytoscape plugin for visualizing data as functional landscapes projected onto biological networks. Bioinformatics. vol. 29 (19).
- (2013) Cooperative RNA polymerase molecules behavior on a stochastic sequence-dependent model for transcription elongation. PLoS ONE. vol. 8.
- (2013) Unravelling the Neospora caninum secretome through the secreted fraction (ESA) and quantification of the discharged tachyzoite using high-resolution mass spectrometry-based proteomics. Parasites & Vectors. vol. 6.
- (2012) HTRIdb: an open-access database for experimentally verified human transcriptional regulation interactions. BMC Genomics. vol. 13.
- (2010) A machine learning approach for genome-wide prediction of morbid and druggable human genes based on systems-level data. BMC Genomics. vol. 11 (S9).
- (2009) Towards the prediction of essential genes by integration of network topology, cellular localization and biological process information. BMC Bioinformatics. vol. 10.
- (2008) In silico network topology-based prediction of gene essentiality. Physica A: Statistical Mechanics and its Applications. vol. 387.