Search results for " BioInformatics."
showing 10 items of 65 documents
Insects and fungi: ecological interactions and functional biodiversity
Mapreduce in computational biology via hadoop and spark
2017
Bioinformatics has a long history of software solutions developed on multi-core computing systems for solving computational intensive problems. This option suffer from some issues solvable by shifting to Distributed Systems. In particular, the MapReduce computing paradigm, and its implementations, Hadoop and Spark, is becoming increasingly popular in the Bioinformatics field because it allows for virtual-unlimited horizontal scalability while being easy-to-use. Here we provide a qualitative evaluation of some of the most significant MapReduce bioinformatics applications. We also focus on one of these applications to show the importance of correctly engineering an application to fully exploi…
Textual data compression in computational biology: Algorithmic techniques
2012
Abstract In a recent review [R. Giancarlo, D. Scaturro, F. Utro, Textual data compression in computational biology: a synopsis, Bioinformatics 25 (2009) 1575–1586] the first systematic organization and presentation of the impact of textual data compression for the analysis of biological data has been given. Its main focus was on a systematic presentation of the key areas of bioinformatics and computational biology where compression has been used together with a technical presentation of how well-known notions from information theory have been adapted to successfully work on biological data. Rather surprisingly, the use of data compression is pervasive in computational biology. Starting from…
A motif-independent metric for DNA sequence specificity
2011
Abstract Background Genome-wide mapping of protein-DNA interactions has been widely used to investigate biological functions of the genome. An important question is to what extent such interactions are regulated at the DNA sequence level. However, current investigation is hampered by the lack of computational methods for systematic evaluating sequence specificity. Results We present a simple, unbiased quantitative measure for DNA sequence specificity called the Motif Independent Measure (MIM). By analyzing both simulated and real experimental data, we found that the MIM measure can be used to detect sequence specificity independent of presence of transcription factor (TF) binding motifs. We…
Bayesian versus data driven model selection for microarray data
2014
Clustering is one of the most well known activities in scientific investigation and the object of research in many disciplines, ranging from Statistics to Computer Science. In this beautiful area, one of the most difficult challenges is a particular instance of the model selection problem, i.e., the identification of the correct number of clusters in a dataset. In what follows, for ease of reference, we refer to that instance still as model selection. It is an important part of any statistical analysis. The techniques used for solving it are mainly either Bayesian or data-driven, and are both based on internal knowledge. That is, they use information obtained by processing the input data. A…
Computational Approaches: Drug Discovery and Design in Medicinal Chemistry and Bioinformatics
2021
To date, computational approaches have been recognized as a key component in drug design and discovery workflows. Developed to help researchers save time and reduce costs, several computational tools have been developed and implemented in the last twenty years. At present, they are routinely used to identify a therapeutic target, understand ligand–protein and protein–protein interactions, and identify orthosteric and allosteric binding sites, but their primary use remains the identification of hits through ligand-based and structure-based virtual screening and the optimization of lead compounds, followed by the estimation of the binding free energy. The repurposing of an old drug for the tr…
Unreliable predictions about COVID‐19 infections and hospitalizations make people worry: The case of Italy
2021
The ten grand challenges of synthetic life
2011
The construction of artificial life is one of the main scientific challenges of the Synthetic Biology era. Advances in DNA synthesis and a better understanding of regulatory processes make the goal of constructing the first artificial cell a realistic possibility. This would be both a fundamental scientific milestone and a starting point of a vast range of applications, from biofuel production to drug design. However, several major issues might hamper the objective of achieving an artificial cell. From the bottom-up to the selection-based strategies, this work encompasses the ten grand challenges synthetic biologists will have to be aware of in order to cope with the task of creating life i…
An Intelligent System for Decision Support in Bioinformatics
2011
The enormous array of computational techniques and data available due to today's use of high-throughput technologies can be quite overwhelming for researchers investigating biological problems. For any problem, there are many possible models and algorithms giving different results. We present a new Intelligent System that supports the selection, configuration and operation of strategies and tools in the bioinformatics domain. The Institute for High Performance Computing and Networking (ICAR-CNR) and the University of Palermo are developing an intelligent system that supports bioinformatics research. The system guides the researcher in building a data analysis workflow and acts as an interfa…
A Knowledge Based Decision Support System for Bioinformatics and System Biology
2011
In this paper, we present a new Decision Support System for Bioinformatics and System Biology issues. Our system is based on a Knowledge base, representing the expertise about the application domain, and a Reasoner. The Reasoner, consulting the Knowledge base and according to the user’s request, is able to suggest one or more strategies in order to resolve the selected problem. Moreover, the system can build, at different abstraction layers, a workflow for the current problem on the basis of the user’s choices, freeing the user from implementation details and assisting him in the correct configuration of the algorithms. Two possible application scenarios will be introduced: the analysis of …