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Here practical aspects of conducting research via computer simulations are discussed. The following issues are addressed: software engineering, object-oriented software development, programming style, macros, make files, scripts, libraries,…

Condensed Matter · Physics 2009-02-02 Alexander K. Hartmann , Heiko Rieger

Rearrangements of bacterial chromosomes can be studied mathematically at several levels, most prominently at a local, or sequence level, as well as at a topological level. The biological changes involved locally are inversions, deletions,…

Group Theory · Mathematics 2013-12-10 Andrew R. Francis

Four chapters of the synthesis represent four major areas of my research interests: 1) data analysis in molecular biology, 2) mathematical modeling of biological networks, 3) genome evolution, and 4) cancer systems biology. The first…

Quantitative Methods · Quantitative Biology 2014-04-08 Andrei Zinovyev

The first step in any genome assembly algorithm entails the conversion from the domain of strings and overlaps to the language of graphs and paths, typically using one of the two conventional methods: de Bruijn graphs or overlap graphs.…

Genomics · Quantitative Biology 2026-04-27 Anton Bankevich

This paper surveys foundation models for AI-enabled biological design, focusing on recent developments in applying large-scale, self-supervised models to tasks such as protein engineering, small molecule design, and genomic sequence design.…

Artificial Intelligence · Computer Science 2025-05-20 Asher Moldwin , Amarda Shehu

Computational methods are the most effective tools we have besides scientific experiments to explore the properties of complex biological systems. Progress is slowing because digital silicon computers have reached their limits in terms of…

Quantum Physics · Physics 2020-04-03 Viv Kendon

Novel technologies in genomics allow creating data in exascale dimension with relatively minor effort of human and laboratory and thus monetary resources compared to capabilities only a decade ago. While the availability of this data…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-11-10 Sandra Gesing , Thomas Richard Connor , Ian Taylor

The article describes the method of using computer-learning tools during the modeling of biological processes in the high school. The author developed web pages for online processing of the results of simulation of the genetic structure of…

Computers and Society · Computer Science 2018-12-04 Olena V. Komarova

The study of system complexity primarily has two objectives: to explore underlying patterns and to develop theoretical explanations. Pattern exploration seeks to clarify the mechanisms behind the emergence of system complexity, while…

Multiagent Systems · Computer Science 2026-02-18 Xiao Xue , Deyu Zhou , Ming Zhang , Xiangning Yu , Fei-Yue Wang

Over the past two decades, a series of works have aimed at studying the problem of genome assembly: the process of reconstructing a genome from sequence reads. An early formulation of the genome assembly problem showed that genome…

Genomics · Quantitative Biology 2013-12-30 Henry Lin

Biological and artificial information processing systems form representations of the world that they can use to categorize, reason, plan, navigate, and make decisions. How can we measure the similarity between the representations formed by…

We discuss a model of genome as a program with functional architecture and consider the approach to Darwinian evolution as a learning problem for functional programming. In particular we introduce a model of learning for some class of…

Neural and Evolutionary Computing · Computer Science 2020-06-18 S. V. Kozyrev

De novo genome assembly is challenging in highly repetitive regions; however, reference-guided assemblers often suffer from bias. We propose a framework for pangenome-guided sequence assembly, which can resolve short-read data in complex…

Quantum Physics · Physics 2026-02-11 Josh Cudby , James Bonfield , Chenxi Zhou , Richard Durbin , Sergii Strelchuk

Computing in the life sciences has undergone a transformative evolution, from early computational models in the 1950s to the applications of artificial intelligence (AI) and machine learning (ML) seen today. This paper highlights key…

Other Quantitative Biology · Quantitative Biology 2024-06-21 Samuel A. Donkor , Matthew E. Walsh , Alexander J. Titus

Computer-aided design for synthetic biology promises to accelerate the rational and robust engineering of biological systems; it requires both detailed and quantitative mathematical and experimental models of the processes to (re)design,…

Machine learning is a modern approach to problem-solving and task automation. In particular, machine learning is concerned with the development and applications of algorithms that can recognize patterns in data and use them for predictive…

Agent-based modeling (ABM) is a powerful computational approach for studying complex biological and biomedical systems, yet its widespread use remains limited by significant computational demands. As models become increasingly…

Quantitative Methods · Quantitative Biology 2025-04-17 Kerri-Ann Norton , Daniel Bergman , Harsh Vardhan Jain , Trachette Jackson

Computing has revolutionized the biological sciences over the past several decades, such that virtually all contemporary research in the biosciences utilizes computer programs. The computational advances have come on many fronts, spurred by…

Other Quantitative Biology · Quantitative Biology 2021-08-23 Berk Ekmekci , Charles E. McAnany , Cameron Mura

Complex systems with tightly coadapted parts frequently appear in living systems and are difficult to account for through Darwinian evolution, that is random variation and natural selection, if the constituent parts are independently coded…

Adaptation and Self-Organizing Systems · Physics 2007-05-23 John F. McGowan , Ph. D

Computer simulations have become a very powerful tool for scientific research. Given the vast complexity that comes with many open scientific questions, a purely analytical or experimental approach is often not viable. For example,…

Neural and Evolutionary Computing · Computer Science 2016-07-12 Roman Bauer , Lukas Breitwieser , Alberto Di Meglio , Leonard Johard , Marcus Kaiser , Marco Manca , Manuel Mazzara , Max Talanov