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Preface. Basic Concepts of Fluid Flow.- Introduction to Numerical Methods.- Finite Difference Methods.- Finite Volume Methods.- Solution of Linear Equation Systems.- Methods for Unsteady Problems.- Solution of the Navier...

Digital technologies have revolutionized studying, analyzing, and interpreting human culture, history, and society. Digital humanities (DH) combine traditional disciplines such as literature, history, and philosophy with...

At any time humans need accurate information to solve different problems. For example, how to perform a task, what happens in the news, what the hundreds of tweets say, etc. On the other hand, electronic information has ...

This thesis, entitled €High Performance Computing for solving large sparse systems. Optical Diffraction Tomography as a case of study€ investigates the computational issues related to the resolution of linear systems o...

BACKGROUND: Recent advances in proteomics technologies such as two-hybrid, phage display and mass spectrometry have enabled us to create a detailed map of biomolecular interaction networks. Initial mapping efforts have a...

The simultaneous measurement of multiple modalities represents an exciting frontier for single-cell genomics and necessitates computational methods that can define cellular states based on multimodal data. Here, we intro...

Importance: Deep learning is a family of computational methods that allow an algorithm to program itself by learning from a large set of examples that demonstrate the desired behavior, removing the need to specify rules ...

With its theoretical basis firmly established in molecular evolutionary and population genetics, the comparative DNA and protein sequence analysis plays a central role in reconstructing the evolutionary histories of spec...

The Bioconductor project is an initiative for the collaborative creation of extensible software for computational biology and bioinformatics. The goals of the project include: fostering collaborative development and wide...

Comparative analysis of molecular sequence data is essential for reconstructing the evolutionary histories of species and inferring the nature and extent of selective forces shaping the evolution of genes and species. He...

"This work describes the use of entomological studies combined with in silico models (computer simulations derived from numerical models) to assess the efficacy of a novel device for controlled release of spatial repel...

"The steel industry faces increasing challenges in managing product diversity, maintaining competitiveness, and improving operational efficiency. Within this context, recommendation systems present a promising opportunit...

A new sequential data assimilation method is discussed. It is based on forecasting the error statistics using Monte Carlo methods, a better alternative than solving the traditional and computationally extremely demanding...

The CCP4 (Collaborative Computational Project, number 4) program suite is a collection of programs and associated data and subroutine libraries which can be used for macromolecular structure determination by X-ray crysta...

Metaheuristics are used as very good optimization methods and they imitate natural, biologic, social and cultural process. In this work, we evaluate and compare three different metaheuristics which are population-based: ...

Early applications of Ant Colony Optimization (ACO) have been mainly concerned with solving ordering problems (e.g., the Traveling Salesperson Problem). More recently, promising results were obtained for solving the Mult...

The resolution of optimization problems is of great interest nowadays and has encouraged the development of various information technology methods to attempt solving them. There are several problems related to Software E...

The resolution of optimization problems is of great interest nowadays and has encouraged the development of various information technology methods to attempt solving them. There are several problems related to Software E...

Protein quantification without isotopic labels has been a long-standing interest in the proteomics field. However, accurate and robust proteome-wide quantification with label-free approaches remains a challenge. We devel...

The caret package, short for classification and regression training, contains numerous tools for developing predictive models using the rich set of models available in R. The package focuses on simplifying model training...

CHARMM (Chemistry at HARvard Molecular Mechanics) is a highly versatile and widely used molecular simulation program. It has been developed over the last three decades with a primary focus on molecules of biological inte...

A flexible statistical framework is developed for the analysis of read counts from RNA-Seq gene expression studies. It provides the ability to analyse complex experiments involving multiple treatment conditions and block...

Recently, several models based on deep neural networks have achieved great success in terms of both reconstruction accuracy and computational performance for single image super-resolution. In these methods, the low resol...

Convolutional networks are at the core of most state of-the-art computer vision solutions for a wide variety of tasks. Since 2014 very deep convolutional networks started to become mainstream, yielding substantial gains ...