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Physical modeling is increasingly important for generating insights into intracellular processes. We describe situations in which combined spatial and stochastic aspects of chemical reactions are needed to capture the relevant dynamics of biochemical systems.
Widely used behavioral assays need re-evaluation and validation against their intended use. We focus here on measures of chronic anxiety in mouse models and posit that widely used assays such as the open-field test are performed at the wrong time, for inadequate durations and using inappropriate mouse strains. We propose that behavioral assays be screened for usefulness on the basis of their replicability across laboratories.
Many scholars claim there is a consensus on broad consent for biobanking. We analyzed the literature in PubMed and found no evidence for consensus. Public perception studies report mixed findings on consent, but many biobanks adopt broad consent. A belief in consensus may stem from knowledge of biobank consent practices.
Driven by the importance of spatial and physical factors in cellular processes and the size and complexity of modern image data, computational analysis of biological imagery has become a vital emerging sub-discipline of bioinformatics and computer vision.
We discuss the advantages and challenges of the open-source strategy in biological image analysis and argue that its full impact will not be realized without better support and recognition of software engineers' contributions to the biological sciences and more support of this development model from funders and institutions.
Bioimaging software developed in a research setting often is not widely used by the scientific community. We suggest that, to maximize both the public's and researchers' investments, usability should be a more highly valued goal. We describe specific characteristics of usability toward which bioimaging software projects should aim.
Informatics has driven mass spectrometry–based protein analysis to create large-scale methods for proteomics. As software algorithms have developed, comparisons between algorithms are inevitable. We outline steps for fair and objective comparisons that will make true innovations apparent.
