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Details

  • Name

    Rui Camacho
  • Cluster

    Computer Science
  • Role

    Senior Researcher
  • Since

    01st January 2011
001
Publications

2018

Using multi-relational data mining to discriminate blended therapy efficiency on patients based on log data

Authors
Rocha, A; Camacho, R; Ruwaard, J; Riper, H;

Publication
Internet Interventions

Abstract

2018

EvoPPI: A Web Application to Compare Protein-Protein Interactions (PPIs) from Different Databases and Species

Authors
Vázquez, N; Rocha, S; Fernández, HL; Torres, A; Camacho, R; Riverola, FF; Vieira, J; Vieira, CP; Jato, MR;

Publication
Practical Applications of Computational Biology and Bioinformatics, 12th International Conference, PACBB 2018, Toledo, Spain, 20-22 May, 2018.

Abstract
Biological processes are mediated by protein-protein interactions (PPI) that have been studied using different methodologies, and organized as centralized repositories - PPI databases. The data stored in the different PPI databases only overlaps partially. Moreover, some of the repositories are dedicated to a species or subset of species, not all have the same functionalities, or store data in the same format, making comparisons between different databases difficult to perform. Therefore, here we present EvoPPI (http://evoppi.i3s.up.pt), an open source web application tool that allows users to compare the protein interactions reported in two different interactomes. When interactomes belong to different species, a versatile BLAST search approach is used to identify orthologous/paralogous genes, which to our knowledge is a unique feature of EvoPPI. © Springer Nature Switzerland AG 2019.

2018

LearnSec: A Framework for Full Text Analysis

Authors
Goncalves, C; Iglesias, EL; Borrajo, L; Camacho, R; Seara Vieira, AS; Goncalves, CT;

Publication
HYBRID ARTIFICIAL INTELLIGENT SYSTEMS (HAIS 2018)

Abstract
Large corpus of scientific research papers have been available for a long time. However, most of those corpus store only the title and the abstract of the paper. For some domains this information may not be enough to achieve high performance in text mining tasks. This problem has been recently reduced by the growing availability of full text scientific research papers. A full text version provides more detailed information but, on the other hand, a large amount of data needs to be processed. A priori, it is difficult to know if the extra work of the full text analysis has a significant impact in the performance of text mining tasks, or if the effect depends on the scientific domain or the specific corpus under analysis. The goal of this paper is to show a framework for full text analysis, called LearnSec, which incorporates domain specific knowledge and information about the content of the document sections to improve the classification process with propositional and relational learning. To demonstrate the usefulness of the tool, we process a scientific corpus based on OSHUMED, generating an attribute/value dataset in Weka format and a First Order Logic dataset in Inductive Logic Programming (ILP) format. Results show a successful assessment of the framework.

2017

QmihR: Pipeline for Quantification of Microbiome in Human RNA-seq

Authors
Cavadas, B; Ferreira, J; Camacho, R; Fonseca, NA; Pereira, L;

Publication
11th International Conference on Practical Applications of Computational Biology & Bioinformatics, PACBB 2017, Porto, Portugal, 21-23 June, 2017

Abstract

2017

Learning influential genes on cancer gene expression data with stacked denoising autoencoders

Authors
Teixeira, V; Camacho, R; Ferreira, PG;

Publication
2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017, Kansas City, MO, USA, November 13-16, 2017

Abstract

Supervised
thesis

2017

Data Mining for Rational Drug Design

Author
Catarina Isabel Peixoto Candeias

Institution
UP-FEUP

2017

Data Mining para análise dos resultados de Gene Expression

Author
Luís Miguel Barroso Natividade

Institution
UP-FEUP

2017

Gait Analysis and Rehabilitation using Inertial Sensors

Author
Patrícia Loureiro Rodrigues

Institution
UP-FEUP

2017

Predicting Adverse Effects of Drugs

Author
Sofia Alexandra Machado Novais

Institution
UP-FEUP

2017

Previsão da evolução de doença oncológica a partir da análise de imagens de PET scan

Author
Miguel José Melo Tavares

Institution
UP-FEUP