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Subjects / keywords: differential equations, computational methods, numerical linear algebra, optimal control; Technology: Technology (General): Industrial engineering. Management engineering: Applied mathematics. Quantitative methods

Subjects / keywords: social sciences, computational economics, statistics, computers, education; Science: Mathematics: Instruments and machines: Electronic computers. Computer science; Social Sciences: Social sciences (General)

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...

Subjects / keywords: computer simulation, computational methods, process control, instrumentation, multiscale experiments; Science: Mathematics: Instruments and machines: Electronic computers. Computer science: Computer software

Subjects / keywords: computational methods, mathematical methods, applied mathematics, computational mathematics, numerical methods; Science: Mathematics; Technology: Technology (General): Industrial engineering. Management engineering: Appl...

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...

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...

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...

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 ...

Despite recent advances achieved by application of high-performance computing methods and novel algorithmic techniques to maximum likelihood (ML)-based inference programs, the major computational bottleneck still consist...

Profile hidden Markov models (profile HMMs) and probabilistic inference methods have made important contributions to the theory of sequence database homology search. However, practical use of profile HMM methods has been...

(NOTE: Each chapter begins with an Introduction, and concludes with Exercises and References.) I. GETTING STARTED. 1. Aspects of Multivariate Analysis. Applications of Multivariate Techniques. The Organization of Data. D...

Edwin Hutchins combines his background as an anthropologist and an open ocean racing sailor and navigator in this account of how anthropological methods can be combined with cognitive theory to produce a new reading of c...

Summary Recent work by Reiss and Ogden provides a theoretical basis for sometimes preferring restricted maximum likelihood (REML) to generalized cross-validation (GCV) for smoothing parameter selection in semiparametric ...