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Subjects / keywords: modeling, algorithms, simulations, software; Science: Mathematics: Instruments and machines: Electronic computers. Computer science

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...

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...

An Introduction to the Bootstrap arms scientists and engineers as well as statisticians with the computational techniques they need to analyze and understand complicated data sets. The bootstrap is a computer-based metho...

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...

BACKGROUND: The Avogadro project has developed an advanced molecule editor and visualizer designed for cross-platform use in computational chemistry, molecular modeling, bioinformatics, materials science, and related are...

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...

BACKGROUND: In a previous paper, we introduced MUSCLE, a new program for creating multiple alignments of protein sequences, giving a brief summary of the algorithm and showing MUSCLE to achieve the highest scores reporte...

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...

Artificial neural net models have been studied for many years in the hope of achieving human-like performance in the fields of speech and image recognition. These models are composed of many nonlinear computational eleme...

Anomaly detection is an important problem that has been researched within diverse research areas and application domains. Many anomaly detection techniques have been specifically developed for certain application domains...

(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...

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...

In the last few years, the deep learning (DL) computing paradigm has been deemed the Gold Standard in the machine learning (ML) community. Moreover, it has gradually become the most widely used computational approach in ...

Subjects / keywords: numerical methods, computational techniques applied to em field problems, coupled field problems, optimization techniques, propagation and diffraction; Science: Physics: Electricity and magnetism

Subjects / keywords: non-linear phenomena, computational techniques, differential equations; Science: Mathematics

Subjects / keywords: non-linear phenomena, computational techniques, differential equations; Science: Mathematics

BACKGROUND: Gene-expression analysis is increasingly important in biological research, with real-time reverse transcription PCR (RT-PCR) becoming the method of choice for high-throughput and accurate expression profiling...

BACKGROUND: Gene set enrichment (GSE) analysis is a popular framework for condensing information from gene expression profiles into a pathway or signature summary. The strengths of this approach over single gene analysis...