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In today's world of big data, computational analysis has become a key driver of biomedical research. Recent exponential growth in the volume of available omics data has reshaped the landscape of contemporary biology, creating demand for a…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-12-09 Jaqueline J. Brito , Thiago Mosqueiro , Jeremy Rotman , Victor Xue , Douglas J. Chapski , Juan De la Hoz , Paulo Matias , Lana Martin , Alex Zelikovsky , Matteo Pellegrinni , Serghei Mangul

Bayesian optimization has become widely popular across various experimental sciences due to its favorable attributes: it can handle noisy data, perform well with relatively small datasets, and provide adaptive suggestions for sequential…

Other Quantitative Biology · Quantitative Biology 2025-08-15 Maximilian Siska , Emma Pajak , Katrin Rosenthal , Antonio del Rio Chanona , Eric von Lieres , Laura Marie Helleckes

In the past decade, enormous progress has been made in advancing the state-of-the-art in bioimage analysis - a young computational field that works in close collaboration with the life sciences on the quantitative analysis of scientific…

Other Quantitative Biology · Quantitative Biology 2023-07-11 Joran Deschamps , Damian Dalle Nogare , Florian Jug

SMeagol is a software tool to simulate highly realistic microscopy data based on spatial systems biology models, in order to facilitate development, validation, and optimization of advanced analysis methods for live cell single molecule…

Biological Physics · Physics 2017-05-08 Martin Lindén , Vladimir Ćurić , Alexis Boucharin , David Fange , Johan Elf

Quasi Static Elasticity Imaging (QSEI) aims to computationally reconstruct the inhomogeneous distribution of the elastic modulus using a measured displacement field. QSEI is a well-established imaging modality used in medical imaging for…

Computational Physics · Physics 2018-02-27 Danny Smyl , Sven Bossuyt , Dong Liu

The `equation-free toolbox' empowers the computer-assisted analysis of complex, multiscale systems. Its aim is to enable you to immediately use microscopic simulators to perform macro-scale system level tasks and analysis, because…

Mathematical Software · Computer Science 2020-04-08 John Maclean , J. E. Bunder , A. J. Roberts

With high-throughput biotechnologies generating unprecedented quantities of data, researchers are faced with the challenge of locating and comparing an exponentially growing number of programs and websites dedicated to computational…

Optical biosensors based on micro-/nano-fibers are highly valuable for probing and monitoring liquid environments and bioactivity. Most of current optical biosensors, however, are still based on glass, semiconductors, or metallic materials,…

Optics · Physics 2025-02-27 X. Yang , L. Xu , S. Xiong , H. Rao , F. Tan , J. Yan , Y. Bao , A. Albanese , A. Camposeo , D. Pisignano , B. Li

Programming is ubiquitous in applied biostatistics; adopting software engineering skills will help biostatisticians do a better job. To explain this, we start by highlighting key challenges for software development and application in…

Summary: R and Matlab are two high-level scientific programming languages which are frequently applied in computational biology. To extend the wide variety of available and approved implementations, we present the Rcall interface which runs…

Programming Languages · Computer Science 2021-06-16 Janine Egert , Clemens Kreutz

BioSimplify is an open source tool written in Java that introduces and facilitates the use of a novel model for sentence simplification tuned for automatic discourse analysis and information extraction (as opposed to sentence simplification…

Computation and Language · Computer Science 2011-07-29 Siddhartha Jonnalagadda , Graciela Gonzalez

Simulated microbial communities are used in benchmarking microbial abundance estimators and other bioinformatic utilities. To match current data scales, large simulated samples are needed, and many. The speed of current implementations…

Quantitative Methods · Quantitative Biology 2025-11-20 Amit Lavon

Photoacoustic (PA) imaging systems based on clinical linear ultrasound arrays have become increasingly popular in translational PA research. Such systems can be more easily integrated in a clinical workflow due to the simultaneous access to…

Numerical simulations are ubiquitous in mathematics and computational science. Several industrial and clinical applications entail modeling complex multiphysics systems that evolve over a variety of spatial and temporal scales. This study…

Mathematical Software · Computer Science 2022-11-14 Pasquale Claudio Africa

Manycore System-on-Chip include an increasing amount of processing elements and have become an important research topic for improvements of both hardware and software. While research can be conducted using system simulators, prototyping…

Hardware Architecture · Computer Science 2013-04-19 Stefan Wallentowitz , Philipp Wagner , Michael Tempelmeier , Thomas Wild , Andreas Herkersdorf

Modern biomedical applications often involve time-series data, from high-throughput phenotyping of model organisms, through to individual disease diagnosis and treatment using biomedical data streams. Data and tools for time-series analysis…

Databases · Computer Science 2019-05-06 Ben D. Fulcher , Carl H. Lubba , Sarab S. Sethi , Nick S. Jones

Scientific applications produce a huge amount of data, which imposes serious management and analysis challenges. In particular, limitations in current database management systems prevent their adoption in simulation applications, in which…

Databases · Computer Science 2019-03-18 Hermano Lustosa , Fabio Porto

Branch is a web application that provides users with no programming with the ability to interact directly with large biomedical datasets. The interaction is mediated through a collaborative graphical user interface for building and…

Applications · Statistics 2016-05-04 Karthik Gangavarapu , Vyshakh Babji , Tobias Meißner , Andrew I. Su , Benjamin M. Good

BayesOpt is a library with state-of-the-art Bayesian optimization methods to solve nonlinear optimization, stochastic bandits or sequential experimental design problems. Bayesian optimization is sample efficient by building a posterior…

Machine Learning · Computer Science 2014-05-30 Ruben Martinez-Cantin