António Cardoso Costa

Understanding the functional sequelae of amino-acid replacements is of fundamental importance in medical genetics. Perhaps, the most intuitive way to assess the potential pathogenicity of a given human missense variant is by measuring the degree of evolutionary conservation of the substituted amino-acid residue, a feature that generally serves as a good proxy metric for the functional/structural importance of that residue. However, the presence of putatively compensated variants as the wild-type alleles in orthologous proteins of other mammalian species not only challenges this classical view of amino-acid essentiality but also precludes the accurate evaluation of the functional impact of this type of missense variant using currently available bioinformatic prediction tools. Compensated variants constitute at least 4% of all known missense variants causing human-inherited disease and hence represent an important potential source of error in that they are likely to be disproportionately misclassified as benign variants. The consequent under-reporting of compensated variants is exacerbated in the context of next-generation sequencing where their inappropriate exclusion constitutes an unfortunate natural consequence of the filtering and prioritization of the very large number of variants generated. Here we demonstrate the reduced performance of currently available pathogenicity prediction tools when applied to compensated variants and propose an alternative machine-learning approach to assess likely pathogenicity for this particular type of variant.

The Informatics Engineering Bologna 1st cycle at ISEP (LEI), which lectures more than 1200 students, has adopted good principles and practices in the major curriculum revision of 2006--2007 (Bologna Process implementation in Portugal). The program uses a mostly practical approach to learning and over 30% of the students have a job, most of them full-time. In 2013 LEI received the EUR-ACE Quality Seal from ENAEE and nowadays is one of the top-rated programs in Portugal in the Informatics area. In the last 9 years, hundreds of students have been exposed to the CDIO Initiative™ (CDIO) practices and 955 students have graduated. CDIO adoption has been essential in terms of learning process effectiveness and graduates' quality. This paper will focus on the importance of LEI curricular capstone-internship activity, how it works and is managed, and the feedback of internship supervisors from companies or R&D units. We believe that LEI's capstone-internship approach can be applied to other engineering programs, with the necessary adaptations to each specific program. This paper addresses relevant educational issues in: Project work in engineering education; First contacts with engineering profession; Improving engineering competences during education; Engineering graduate students competences versus companies professional needs.

Proteins are biochemical entities consisting of one or more blocks typically folded in a 3D pattern. Each block (a polypeptide) is a single linear sequence of amino acids that are biochemically bonded together. The amino acid sequence in a protein is defined by the sequence of a gene or several genes encoded in the DNA-based genetic code. This genetic code typically uses twenty amino acids, but in certain organisms the genetic code can also include two other amino acids. After linking the amino acids during protein synthesis, each amino acid becomes a residue in a protein, which is then chemically modified, ultimately changing and defining the protein function. In this study, the authors analyze the amino acid sequence using alignment-free methods, aiming to identify structural patterns in sets of proteins and in the proteome, without any other previous assumptions. The paper starts by analyzing amino acid sequence data by means of histograms using fixed length amino acid words (tuples). After creating the initial relative frequency histograms, they are transformed and processed in order to generate quantitative results for information extraction and graphical visualization. Selected samples from two reference datasets are used, and results reveal that the proposed method is able to generate relevant outputs in accordance with current scientific knowledge in domains like protein sequence/proteome analysis.

This paper aims to study the relationships between chromosomal DNA sequences of twenty species. We propose a methodology combining DNA-based word frequency histograms, correlation methods, and an MDS technique to visualize structural information underlying chromosomes (CRs) and species. Four statistical measures are tested (Minkowski, Cosine, Pearson product-moment, and Kendall 𝜏 rank correlations) to analyze the information content of 421 nuclear CRs from twenty species. The proposed methodology is built on mathematical tools and allows the analysis and visualization of very large amounts of stream data, like DNA sequences, with almost no assumptions other than the predefined DNA word length. This methodology is able to produce comprehensible three-dimensional visualizations of CR clustering and related spatial and structural patterns. The results of the four test correlation scenarios show that the high-level information clusterings produced by the MDS tool are qualitatively similar, with small variations due to each correlation method characteristics, and that the clusterings are a consequence of the input data and not methods artifacts.

This paper studies the DNA code of eleven mammals from the perspective of fractional dynamics. The application of Fourier transform and power law trendlines leads to a categorical representation of species and chromosomes. The DNA information reveals long range memory characteristics.

This paper studies musical opus from the point of view of three mathematical tools: entropy, pseudo phase plane (PPP), and multidimensional scaling (MDS). The experiments analyze ten sets of different musical styles. First, for each musical composition, the PPP is produced using the time series lags captured by the average mutual information. Second, to unravel hidden relationships between the musical styles the MDS technique is used. The MDS is calculated based on two alternative metrics obtained from the PPP, namely, the average mutual information and the fractal dimension. The results reveal significant differences in the musical styles, demonstrating the feasibility of the proposed strategy and motivating further developments towards a dynamical analysis of musical sounds.