Davide Chicco

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Consistency and completeness of biomolecular annotations is a keypoint of correct interpretation of biological experiments. Yet, the associations between genes (or proteins) and features correctly annotated are just some of all the existing ones. As time goes by, they increase in number and become more useful, but they remain incomplete and some of them(More)
The annotation of genomic information is a major challenge in biology and bioinformatics. Existing databases of known gene functions are incomplete and prone to errors, and the bimolecular experiments needed to improve these databases are slow and costly. While computational methods are not a substitute for experimental verification, they can help in two(More)
Gene function annotations, which are associations between a gene and a term of a controlled vocabulary describing gene functional features, are of paramount importance in modern biology. Datasets of these annotations, such as the ones provided by the Gene Ontology Consortium, are used to design novel biological experiments and interpret their results.(More)
Genomic annotations with functional controlled terms, such as the Gene Ontology (GO) ones, are paramount in modern biology. Yet, they are known to be incomplete, since the current biological knowledge is far to be definitive. In this scenario, computational methods that are able to support and quicken the curation of these annotations can be very useful. In(More)
Genomic annotations describing structural and functional features of genes and gene products through controlled terminologies and ontologies are extremely valuable, especially for computational analyses aimed at inferring new biomedical knowledge, which rely on available annotations. Yet, they are incomplete, especially for recently studied genomes, and(More)
Truncated Singular Value Decomposition (SVD) has always been a key algorithm in modern machine learning. Scientists and researchers use this applied mathematics method in many fields. Despite a long history and prevalence, the issue of how to choose the best truncation level still remains an open challenge. In this paper, we describe a new algorithm, akin a(More)
Biomolecular annotation databases are very important in modern biomedical and genetic research. Correct interpretation of biological experiments depends on consistency and completeness of such databases. To improve their quality and coverage, computational methods that are able to supply a ranked list of predicted gene or gene products annotations are(More)
Gene function annotations are key elements in biology and bioinformatics. A typical annotation is the association between a gene and a feature term that describes a functional feature of the gene by using a controlled vocabulary term (e.g. a Gene Ontology (GO) feature term). Unfortunately, available annotations contain errors and biologically validated ones(More)
In the computational biology community, machine learning algorithms are key instruments for many applications, including the prediction of gene-functions based upon the available biomolecular annotations. Additionally, they may also be employed to compute similarity between genes or proteins. Here, we describe and discuss a software suite we developed to(More)