Search results for "INFORMATICS"

Detecting significant features in modeling microRNA-target interactions

2017

MicroRNAs (miRNAs) are small non-coding RNA molecules mediating the translational repression and degradation of target mRNAs in the cell. Mature miRNAs are used as a template by the RNA-induced silencing complex (RISC) to recognize the complementary mRNAs to be regulated. Up to 60% of human genes are putative targets of one or more miRNAs. Several prediction tools are available to suggest putative miRNA targets, however, only a small part of the interaction pairs has been validated by experimental approaches. The analysis of the expression profile of the RNA fraction immunoprecipitated (IP) with the RISC proteins is an established method to detect which genes are actually regulated by the R…

Modelling and Simulation in Science, Proceedings of the 6th International Workshop on Data Analysis in Astronomy >

2007

Algorithms in Bioinformatics

2008

Preface

2011

A Fuzzy One Class Classifier for Multi Layer Model

2009

The paper describes an application of a fuzzy one-class classifier (FOC ) for the identification of different signal patterns embedded in a noise structured background. The classification phase is applied after a preprocessing phase based on a Multi Layer Model (MLM ) that provides a preliminary signal segmentation in an interval feature space. The FOC has been tested on synthetic and real microarray data in the specific problem of DNA nucleosome and linker regions identification. Results have shown, in both cases, a good recognition rate.

Algorithmic paradigms for stability-based cluster validity and model selection statistical methods, with applications to microarray data analysis

2012

AbstractThe advent of high throughput technologies, in particular microarrays, for biological research has revived interest in clustering, resulting in a plethora of new clustering algorithms. However, model selection, i.e., the identification of the correct number of clusters in a dataset, has received relatively little attention. Indeed, although central for statistics, its difficulty is also well known. Fortunately, a few novel techniques for model selection, representing a sharp departure from previous ones in statistics, have been proposed and gained prominence for microarray data analysis. Among those, the stability-based methods are the most robust and best performing in terms of pre…

"A KNOWLEDGE-BASED EXPERT SYSTEM IN BIOINFORMATICS: AN APPLICATION TO REVERSE ENGINEERING GENE REGULATORY NETWORK"

2011

The huge amount of biological data has spread the development of plenty of bionformatics tools, databases and web services. In order to face a computational biology problem, there not exist only a way, but different methodologies and strategies, with their own pros and cons, can be applied. In this PhD thesis I present a knowledge-based expert system that aims at helping a bionformatics researcher in the choice of the proper strategy and heuristic in order to resolve a bioinformatics issue. The Knowledge Base of the system is structured by means of an ontology and codes the expertise about the application domain. KB is organized into decision-making modules that introduce a set of metareaso…

An Intelligent System for Building Bioinformatics Workflows

2012

In this paper a new intelligent system designed to support the researcher in the development of a workflow for bio informatics experiments is presented. The proposed system is capable to suggest one or more strategies in order to resolve the selected problem and to support the user in the assembly of a workflow for complex experiments, using a a Knowledge base, representing the expertise about the application domain, and a Rule-Based system for decision-making activity. Moreover, the system can represent this workflow at different abstraction layers, freeing the user from implementation details and assisting him in the correct configuration of the algorithms. A sample workflow for protein c…

An Ontology Design Methodology for Knowledge-Based Systems with Application to Bioinformatics

2012

Ontologies are formal knowledge representation models. Knowledge organization is a fundamental requirement in order to develop Knowledge-Based systems. In this paper we present Data-Problem-Solver (DPS) approach, a new ontological paradigm that allows the knowledge designer to model and represent a Knowledge Base (KB) for expert systems. Our approach clearly distinguishes among the knowledge about a problem to resolve (answering the what to do question), the solver method to resolve it (answering the how to do question) and the type of input data required (answering the what I need question). The main purpose of the proposed paradigm is to facilitate the generalization of the application do…

On-Line Retrieval of Health Information Based on Language Complexity, Information Customization and Information Quality

2021

Abstract. A patient, nowadays, acquires on-line health information mainly by means of a search engine. Generic search engines have been shown to be limited and unsatisfactory, at times, because of their generic searches that overload users with the amount of results. Moreover, they are not able to provide customized information to different types of users. At the same time, specific search engines mostly work on medical literature and provide extracts from medical journals that are mainly useful for medical researchers and experts. As a consequence, the found health information may or may not help a user (mainly a non-expert one) for a full comprehension of what he/she is looking for (e.g.,…