CV Lattes
GoogleMyCitations
ResearcherID
ORCID
Fundação Antonio Prudente (FAP). A C Camargo Cancer Center (Institutional affiliation for the last research proposal) Birthplace: Brazil
graduate at Ciência da Computação from Universidade Paulista (2001). Has experience in Computer Science, focusing on Core Software, acting on the following subjects: bioinformatics, bioinformática, polybayes, single nucleotide polymorphism (snp) and gene expression. (Source: Lattes Curriculum)
| News published in Agência FAPESP Newsletter about the researcher |
| TITULO |
| Articles published in other media outlets (0 total): |
| More itemsLess items |
| VEICULO: TITULO (DATA) |
| VEICULO: TITULO (DATA) |
The overall response rate (ORR) in patients treated with immune checkpoints varies greatly and ranges from 30% (Head and Neck cancer) to as high as 60% as a first line therapy in malignant melanoma. Non-small cell lung cancer (NSCLC) patients treated with checkpoint inhibition therapy is up to 45% as first line therapy. The elucidation of the factors responsible for treatment failure is f…
INCiTO-INOTE will continue to support the scientific program previously created by the INCiTO, exploring bench-to-bedside-to-bench concepts, in order to face the challenges that are still limiting cancer prevention, diagnosis and treatment. The Institute will explore its large experience in genetics, epigenetics “comics”, bioinformatics and biomarkers to focus in areas where it can be wor…
Retrotransposable or Mobile Elements (MEs) comprise a constant threat to host genome due to their spontaneous mutational capabilities in DNA. To ensure such a level of propagation, a family of nucleic acid-modifying enzymes acts to mobilize the deleterious effects of the MEs. However, what could be regarded as a mechanism of protection to the integrity of the genome may be a source of chr…
Race refers to a population with common genetic and phenotypic features that separate them from other populations. Population studies suggest biological differences between races, in multiple aspects, such as: mutations, obesity, chronic inflammation and immune system, being, therefore, a relevant factor to be considered in the emergence and progression of diseases. Melanoma and non-small…
The human microbiome is the group established between the interactions of body sites and the microbes communities that reside within. With the advances in molecular technologies, the existence of a great microorganisms diversity that wasn't detected before was revealed. Thus, new evidence of the role of microorganisms in host health was emerging. The study of the interaction between micro…
Gastric Adenocarcinomas (GAs) are highly aggressive neoplasms with a high incidence in Brazil. The highest world rates of GA's mortality are due to few clinical signs of the disease in its early stages, which leads to late detection in most cases. Because of strong genetic and environmental component in GA etiology, the search for the causing somatic mutations processes that contribute …
| 2 / 2 | Ongoing research grants |
| 1 / 1 | Completed research grants |
| 4 / 3 | Completed scholarships in Brazil |
| 7 / 6 | All research grants and scholarships |
| Associated processes | |
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
| Publications | 5 |
| Citations | 19 |
| Cit./Article | 3.8 |
| Data from Web of Science | |
ROSALES, RAFAEL A.; DRUMMOND, RODRIGO D.; VALIERIS, RENAN; DIAS-NETO, EMMANUEL; DA SILVA, ISRAEL T.. signeR: an empirical Bayesian approach to mutational signature discovery. Bioinformatics, v. 33, n. 1, p. 8-16, JAN 1 2017. Web of Science Citations: 19. (15/19324-6, 14/26897-0)
VENEZIAN POVOA, LUCAS; RIBEIRO, CARLOS HENRIQUE COSTA; DA SILVA, ISRAEL TOJAL. Machine learning predicts treatment sensitivity in multiple myeloma based on molecular and clinical information coupled with drug response. PLoS One, v. 16, n. 7, JUL 28 2021. Web of Science Citations: 0. (15/19324-6)
POVOA, LUCAS VENEZIAN; BALAN CALVI, URIEL CAIRE; LORENA, ANA CAROLINA; COSTA RIBEIRO, CARLOS HENRIQUE; DA SILVA, ISRAEL TOJAL. A Multi-Learning Training Approach for Distinguishing Low and High Risk Cancer Patients. IEEE ACCESS, v. 9, p. 115453-115465, 2021. Web of Science Citations: 0. (15/19324-6)
BUTTURA, JAQUELINE RAMALHO; PROVISOR SANTOS, MONIZE NAKAMOTO; VALIERIS, RENAN; DRUMMOND, RODRIGO DUARTE; DEFELICIBUS, ALEXANDRE; LIMA, JOAO PAULO; CALSAVARA, VINICIUS FERNANDO; FREITAS, HELANO CARIOCA; CORDEIRO DE LIMA, VLADMIR C.; BARTELLI, THAIS FERNANDA; et al. Mutational Signatures Driven by Epigenetic Determinants Enable the Stratification of Patients with Gastric Cancer for Therapeutic Intervention. CANCERS, v. 13, n. 3, FEB 2021. Web of Science Citations: 0. (15/19324-6, 16/11791-7, 14/26897-0)
VALIERIS, RENAN; AMARO, LUCAS; BUENO DE TOLEDO OSORIO, CYNTHIA APARECIDA; BUENO, ADRIANA PASSOS; ROSALES MITROWSKY, RAFAEL ANDRES; CARRARO, DIRCE MARIA; NUNES, DIANA NORONHA; DIAS-NETO, EMMANUEL; DA SILVA, ISRAEL TOJAL. Deep Learning Predicts Underlying Features on Pathology Images with Therapeutic Relevance for Breast and Gastric Cancer. CANCERS, v. 12, n. 12, DEC 2020. Web of Science Citations: 0. (15/19324-6, 14/26897-0)