58 documents found, page 1 of 6

Federated Learning in Medical Image Analysis: A Systematic Survey

Using multi-relational data mining to discriminate blended therapy efficiency o...

Parallel Algorithms for Multirelational Data Mining: Application to Life Scienc...

Fine Time Scaling of Purifying Selection on Human Nonsynonymous mtDNA Mutations...

A high-resolution mtDNA phylogenetic tree allowed us to look backward in time to investigate purifying selection. Purifying selection was very strong in the last 2,500 years, continuously eliminating pathogenic mutations back until the end of the Younger Dryas (approximate to 11,000 years ago), when a large population expansion likely relaxed selection pressure. This was preceded by a phase of stable selection ...

Improving the performance of Transposable Elements detection tools

Boosting the Detection of Transposable Elements Using Machine Learning

Transposable Elements (TE) are sequences of DNA that move and transpose within a genome. TEs, as mutation agents, are quite important for their role in both genome alteration diseases and on species evolution. Several tools have been developed to discover and annotate TEs but no single one achieves good results on all different types of TEs. In this paper we evaluate the performance of several TEs detection and...

Predicting the secondary structure of proteins using Machine Learning algorithms

The functions of proteins in living organisms are related to their 3-D structure, which is known to be ultimately determined by their linear sequence of amino acids that together form these macromolecules. It is, therefore, of great importance to be able to understand and predict how the protein 3D- structure arises from a particular linear sequence of amino acids. In this paper we report the application of Mac...

Predicting the secondary structure of proteins using Machine Learning algorithms

The functions of proteins in living organisms are related to their 3-D structure, which is known to be ultimately determined by their linear sequence of amino acids that together form these macromolecules. It is, therefore, of great importance to be able to understand and predict how the protein 3D-structure arises from a particular linear sequence of amino acids. In this paper we report the application of Mach...

A relational learning approach to Structure-Activity Relationships in drug desi...

It has been recognized that the development of new therapeutic drugs is a complex and expensive process. A large number of factors affect the activity in vivo of putative candidate molecules and the propensity for causing adverse and toxic effects is recognized as one of the major hurdles behind the current "target-rich, lead-poor" scenario. Structure-Activity Relationship (SAR) studies, using relational Machin...

BioTextRetriever: A Tool to Retrieve Relevant Papers.

Whenever new sequences of DNA or proteins have been decoded it is almost compulsory to look at similar sequences and papers describing those sequences in order to both collect relevant information concerning the function and activity of the new sequences and/or know what is known already about similar sequences. In current web sites and data bases of sequences there are, usually, a set of curated paper referenc...