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Bioinformatics is a new discipline that addresses the need to manage and interpret the data that in the past decade was massively generated by genomic research. This discipline represents the convergence of genomics, biotechnology and…

Computational Engineering, Finance, and Science · Computer Science 2009-11-24 Sabu M. Thampi

The integration of bioinformatics predictions and experimental validation plays a pivotal role in advancing biological research, from understanding molecular mechanisms to developing therapeutic strategies. Bioinformatics tools and methods…

This article highlights some of the basic concepts of bioinformatics and data mining. The major research areas of bioinformatics are highlighted. The application of data mining in the domain of bioinformatics is explained. It also…

Computational Engineering, Finance, and Science · Computer Science 2012-05-08 Khalid Raza

In the last few decades or so, we witness a paradigm shift in our nature studies - from a data-processing based computational approach to an information-processing based cognitive approach. The process is restricted and often misguided by…

Computational Engineering, Finance, and Science · Computer Science 2015-05-20 Emanuel Diamant

Documentation is one of the most neglected activities in Software Engineering, although it is an important method of assuring quality and understanding. Bioinformatics software is generally written by researchers from fields other than…

Software Engineering · Computer Science 2023-05-09 Vinicius Soares Silva Marques , Laurence Rodrigues do Amaral

Integrative biological simulations have a varied and controversial history in the biological sciences. From computational models of organelles, cells, and simple organisms, to physiological models of tissues, organ systems, and ecosystems,…

Quantitative Methods · Quantitative Biology 2017-12-06 Gopal P. Sarma , Victor Faundez

In biomedical research, validation of a new scientific discovery is tied to the reproducibility of its experimental results. However, in genomics, the definition and implementation of reproducibility still remain imprecise. Here, we argue…

The fields of computing and biology have begun to cross paths in new ways. In this paper a review of the current research in biological computing is presented. Fundamental concepts are introduced and these foundational elements are explored…

Computational Engineering, Finance, and Science · Computer Science 2009-11-10 Balaji Akula , James Cusick

Nanoinformatics is a novel, rapidly growing area of research that involves the application of computational techniques to several aspects of research in the field of nanotechnology, especially concerned its application to biotechnology.…

Medical Physics · Physics 2024-01-22 Francisco Mariano-Neto , Thiago de Castro Pereira

Like other types of computational research, modeling and simulation of biological processes (biomodels) is still largely communicated without sufficient detail to allow independent reproduction of results. But reproducibility in this area…

Other Quantitative Biology · Quantitative Biology 2023-04-19 Pedro Mendes

Advances in biology have mostly relied on theories that were subsequently revised, expanded or eventually refuted using experimental and other means. Theoretical biology used to primarily provide a basis to rationally examine the frameworks…

Other Quantitative Biology · Quantitative Biology 2020-05-22 Sepehr Ehsani

Modeling and simulation are recognized as important aspects of the scientific method for more than 70 years but its adoption in biology has been slow. Debates on its representativeness, usefulness, and whether the effort spent on such…

Quantitative Methods · Quantitative Biology 2023-02-21 Maurice HT Ling

Biomedical research centers can empower basic discovery and novel therapeutic strategies by leveraging their large-scale datasets from experiments and patients. This data, together with new technologies to create and analyze it, has ushered…

Study reproducibility is essential to corroborate, build on, and learn from the results of scientific research but is notoriously challenging in bioinformatics, which often involves large data sets and complex analytic workflows involving…

Quantitative Methods · Quantitative Biology 2023-05-22 Christopher R. Keefe , Matthew R. Dillon , Chloe Herman , Mary Jewell , Colin V. Wood , Evan Bolyen , J. Gregory Caporaso

The theoretical analysis of performance has been an important tool in the engineering of algorithms in many application domains. Its goals are to predict the empirical performance of an algorithm and to be a yardstick that drives the design…

Data Structures and Algorithms · Computer Science 2022-11-15 Paul Medvedev

Biology is data-rich, and it is equally rich in concepts and hypotheses. Part of trying to understand biological processes and systems is therefore to confront our ideas and hypotheses with data using statistical methods to determine the…

Quantitative Methods · Quantitative Biology 2022-06-22 Sean T. Vittadello , Michael P. H. Stumpf

Computational biology is on the verge of a paradigm shift in its research practice - from a data-based (computational) paradigm to an information-based (cognitive) paradigm. As in the other research fields, this transition is impeded by…

Other Computer Science · Computer Science 2015-05-21 Emanuel Diamant

Current research in biology heavily depends on the availability and efficient use of information. In order to build new knowledge, various sources of biological data must often be combined. Semantic Web technologies, which provide a common…

Quantitative Methods · Quantitative Biology 2009-02-19 Claude Pasquier

While many good textbooks are available on Protein Structure, Molecular Simulations, Thermodynamics and Bioinformatics methods in general, there is no good introductory level book for the field of Structural Bioinformatics. This book aims…

Biomolecules · Quantitative Biology 2023-07-10 K. Anton Feenstra , Sanne Abeln

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
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