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Cell segmentation is crucial in many image analysis pipelines. This analysis compares many tools on a multimodal cell segmentation benchmark. A Transformer-based model performed best in terms of performance and general applicability.
This analysis provides 108 noncoding CRISPR screens collated by the ENCODE4 consortium and establishes experimental guidelines for future CRISPRi screens characterizing functional cis-regulatory elements.
This analysis leverages experimentally sequenced data and in silico mixtures to simulate transcript expression differences, which enables a performance assessment of long-read tools developed for isoform detection, differential transcript expression analysis and differential transcript usage analysis.
This study describes benchmarking and validation of computational tools for detecting circRNAs, finding most to be highly precise with variations in sensitivity and total detection. The study also finds over 315,000 putative human circRNAs.
This updated analysis of the Cell Tracking Challenge explores how algorithms for cell segmentation and tracking in both 2D and 3D have advanced in recent years, pointing users to high-performing tools and developers to open challenges.
This paper compares different transformation approaches for analysis of single-cell RNA-sequencing data and provides recommendations for method selection.
An international blind study confirms that smFRET measurements on dynamic proteins are highly reproducible across instruments, analysis procedures and timescales, further highlighting the promise of smFRET for dynamic structural biology.
A machine learning competition results in tools for labeling protein patterns of single cells in images with population labels. The winners improve the state of the art and provide strategies to deal with weak classification challenges.
This work presents a comprehensive benchmarking analysis of computational methods that integrates spatial and single-cell transcriptomics data for transcript distribution prediction and cell type deconvolution.
This study presents the results of the second round of the Critical Assessment of Metagenome Interpretation challenges (CAMI II), which is a community-driven effort for comprehensively benchmarking tools for metagenomics data analysis.
This analysis systematically evaluates cross-linking chemistry and chromatin fragmentation strategies commonly used in 3C assays and introduces an improved Hi-C protocol for detecting loops and compartments.
Many computational tools for metagenomic profiling have been developed, with different algorithms and features. This analysis shows that, when comparing these tools, the distinction of different types of relative sequence abundance should be taken into consideration.
This Analysis reports a computational approach to implement Hi-C, SPRITE and GAM, which allows researchers to assess the performances of the three technologies to capture DNA contacts in chromatin three-dimensional models.
Results are presented from the first Critical Assessment of protein Intrinsic Disorder prediction (CAID) experiment, a community-based blind test to determine the state of the art in predicting intrinsically disordered regions in proteins.