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This Perspective discusses the potential of protein structure-prediction models for exploring the structural landscape and specificity of TCR–pMHC interactions.
This Perspective presents a reliable and comprehensive source of information on pitfalls related to validation metrics in image analysis, with an emphasis on biomedical imaging.
Metrics Reloaded is a comprehensive framework for guiding researchers in the problem-aware selection of metrics for common tasks in biomedical image analysis.
This Perspective introduces advances in quantitative phase imaging and artificial intelligence-based image analysis and further describes how the two technologies intersect and synergize to enable biomedical research.
This Perspective introduces the Minimum Information About Disorder Experiments guidelines, which provide a community consensus on the minimum information required to appropriately describe metadata on experimentally and computationally derived structural state(s) of intrinsically disordered proteins or regions.
This Perspective introduces biologists interested in computational approaches to the benefits of the Julia programming language for meeting current and future computational demands.
A community of researchers working in the emerging field of single-cell proteomics propose best-practice experimental and computational recommendations and reporting guidelines for studies analyzing proteins from single cells by mass spectrometry.
This Perspective discusses available software tools for lipidomics data analysis and provides a web-based Lipidomics Tools Guide to help guide the choice of these tools, organized by the major tasks for lipidomics research.
This Perspective describes common pitfalls that can occur when using light sheet microscopy and offers guidance for improved quantitative imaging with these instruments.
In this Perspective, technologies and challenges in the cardiac tissue engineering field are discussed and strategies to overcome these challenges are proposed.
This Perspective offers an overview of organic dyes commonly used as fluorescent labels and gives a chemist’s insight into their benefits and peculiarities.
This Perspective describes advances in computer science that enable the integration of deep learning with traditional knowledge-based modeling in biological sciences, and discusses how such integration might overcome the challenges of modeling sparse, incomplete and noisy experimental data.