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Journal of Biomedical Informatics Sep 2022
Topics: Computational Biology; Genomics; Precision Medicine; Proteomics; Translational Research, Biomedical
PubMed: 35998813
DOI: 10.1016/j.jbi.2022.104170 -
Journal of Biosciences 2022Network architecture plays a crucial role in governing the dynamics of any biological network. Further, network structures have been shown to remain conserved across... (Review)
Review
Network architecture plays a crucial role in governing the dynamics of any biological network. Further, network structures have been shown to remain conserved across organisms for a given phenotype. Therefore, the mapping between network structures and the output functionality not only aids in understanding of biological systems but also finds application in synthetic biology and therapeutics. Based on the approaches involved, most of the efforts hitherto invested in this field can be classified into three broad categories, namely, computational efforts, rule-based methods and systems-theoretic approaches. The present review provides a qualitative and quantitative study of all three approaches in the light of three well-researched biological phenotypes, namely, oscillation, toggle switching, and adaptation. We also discuss the advantages, limitations, and future research scope for all three approaches along with their possible applications to other emergent properties of biological relevance.
Topics: Computational Biology; Systems Biology
PubMed: 36222149
DOI: No ID Found -
Proceedings of the National Academy of... Sep 2005The Arthur M. Sackler Colloquium of the National Academy of Sciences, "Frontiers in Bioinformatics: Unsolved Problems and Challenges," organized by David Eisenberg, Russ... (Review)
Review
The Arthur M. Sackler Colloquium of the National Academy of Sciences, "Frontiers in Bioinformatics: Unsolved Problems and Challenges," organized by David Eisenberg, Russ Altman, and myself, was held October 15-17, 2004, to provide a forum for discussing concepts and methods in bioinformatics serving the biological and medical sciences. The deluge of genomic and proteomic data in the last two decades has driven the creation of tools that search and analyze biomolecular sequences and structures. Bioinformatics is highly interdisciplinary, using knowledge from mathematics, statistics, computer science, biology, medicine, physics, chemistry, and engineering.
Topics: Animals; Computational Biology; Genome, Human; Genomics; Humans; Proteomics; Systems Analysis
PubMed: 16157888
DOI: 10.1073/pnas.0501804102 -
Annals of the New York Academy of... Jan 2017Names in programming are vital for understanding the meaning of code and big data. We define code2brain (C2B) interfaces as maps in compilers and brains between meaning... (Review)
Review
Names in programming are vital for understanding the meaning of code and big data. We define code2brain (C2B) interfaces as maps in compilers and brains between meaning and naming syntax, which help to understand executable code. While working toward an Evolvix syntax for general-purpose programming that makes accurate modeling easy for biologists, we observed how names affect C2B quality. To protect learning and coding investments, C2B interfaces require long-term backward compatibility and semantic reproducibility (accurate reproduction of computational meaning from coder-brains to reader-brains by code alone). Semantic reproducibility is often assumed until confusing synonyms degrade modeling in biology to deciphering exercises. We highlight empirical naming priorities from diverse individuals and roles of names in different modes of computing to show how naming easily becomes impossibly difficult. We present the Evolvix BEST (Brief, Explicit, Summarizing, Technical) Names concept for reducing naming priority conflicts, test it on a real challenge by naming subfolders for the Project Organization Stabilizing Tool system, and provide naming questionnaires designed to facilitate C2B debugging by improving names used as keywords in a stabilizing programming language. Our experiences inspired us to develop Evolvix using a flipped programming language design approach with some unexpected features and BEST Names at its core.
Topics: Biological Ontologies; Brain-Computer Interfaces; Cloud Computing; Computational Biology; Data Mining; Humans; Internet; Programming Languages; Reproducibility of Results; Software; Software Design; Terminology as Topic
PubMed: 27918836
DOI: 10.1111/nyas.13192 -
Journal of Immunology Research 2015
Topics: Allergy and Immunology; Computational Biology; Humans; Models, Immunological
PubMed: 26844232
DOI: 10.1155/2015/170920 -
Expert Review of Molecular Diagnostics Mar 2017The emergence and mass utilization of high-throughput (HT) technologies, including sequencing technologies (genomics) and mass spectrometry (proteomics, metabolomics,... (Review)
Review
The emergence and mass utilization of high-throughput (HT) technologies, including sequencing technologies (genomics) and mass spectrometry (proteomics, metabolomics, lipids), has allowed geneticists, biologists, and biostatisticians to bridge the gap between genotype and phenotype on a massive scale. These new technologies have brought rapid advances in our understanding of cell biology, evolutionary history, microbial environments, and are increasingly providing new insights and applications towards clinical care and personalized medicine. Areas covered: The very success of this industry also translates into daunting big data challenges for researchers and institutions that extend beyond the traditional academic focus of algorithms and tools. The main obstacles revolve around analysis provenance, data management of massive datasets, ease of use of software, interpretability and reproducibility of results. Expert commentary: The authors review the challenges associated with implementing bioinformatics best practices in a large-scale setting, and highlight the opportunity for establishing bioinformatics pipelines that incorporate data tracking and auditing, enabling greater consistency and reproducibility for basic research, translational or clinical settings.
Topics: Computational Biology; Genetic Research; Genomics
PubMed: 28092471
DOI: 10.1080/14737159.2017.1282822 -
Genome Biology Aug 2016
Topics: Access to Information; Computational Biology; Information Dissemination; Licensure; Open Access Publishing; Periodicals as Topic; Software
PubMed: 27520968
DOI: 10.1186/s13059-016-1040-y -
Journal of Structural and Functional... Mar 2016The period 2000-2015 brought the advent of high-throughput approaches to protein structure determination. With the overall funding on the order of $2 billion (in 2010... (Review)
Review
The period 2000-2015 brought the advent of high-throughput approaches to protein structure determination. With the overall funding on the order of $2 billion (in 2010 dollars), the structural genomics (SG) consortia established worldwide have developed pipelines for target selection, protein production, sample preparation, crystallization, and structure determination by X-ray crystallography and NMR. These efforts resulted in the determination of over 13,500 protein structures, mostly from unique protein families, and increased the structural coverage of the expanding protein universe. SG programs contributed over 4400 publications to the scientific literature. The NIH-funded Protein Structure Initiatives alone have produced over 2000 scientific publications, which to date have attracted more than 93,000 citations. Software and database developments that were necessary to handle high-throughput structure determination workflows have led to structures of better quality and improved integrity of the associated data. Organized and accessible data have a positive impact on the reproducibility of scientific experiments. Most of the experimental data generated by the SG centers are freely available to the community and has been utilized by scientists in various fields of research. SG projects have created, improved, streamlined, and validated many protocols for protein production and crystallization, data collection, and functional analysis, significantly benefiting biological and biomedical research.
Topics: Biomedical Research; Computational Biology; Crystallography, X-Ray; Databases, Protein; Genomics; Humans; Magnetic Resonance Spectroscopy; Protein Conformation; Proteins; Proteomics
PubMed: 26935210
DOI: 10.1007/s10969-016-9201-5 -
PLoS Computational Biology Jan 2015
Topics: Computational Biology; Humans
PubMed: 25569585
DOI: 10.1371/journal.pcbi.1004053 -
Briefings in Bioinformatics Mar 2019This review provides a historical overview of the inception and development of bioinformatics research in the Netherlands. Rooted in theoretical biology by foundational... (Review)
Review
This review provides a historical overview of the inception and development of bioinformatics research in the Netherlands. Rooted in theoretical biology by foundational figures such as Paulien Hogeweg (at Utrecht University since the 1970s), the developments leading to organizational structures supporting a relatively large Dutch bioinformatics community will be reviewed. We will show that the most valuable resource that we have built over these years is the close-knit national expert community that is well engaged in basic and translational life science research programmes. The Dutch bioinformatics community is accustomed to facing the ever-changing landscape of data challenges and working towards solutions together. In addition, this community is the stable factor on the road towards sustainability, especially in times where existing funding models are challenged and change rapidly.
Topics: Community Networks; Computational Biology; Humans; Netherlands; Sequence Analysis, DNA; Translational Research, Biomedical
PubMed: 28968694
DOI: 10.1093/bib/bbx087