HiC-Pro is an optimized and flexible pipeline for processing Hi-C data from raw reads to normalized contact maps. HiC-Pro maps reads, detects valid ligation products, performs quality controls and generates intra- and inter-chromosomal contact maps. It includes a fast implementation of the iterative correction method and is based on a memory-efficient data format for Hi-C contact maps. In addition, HiC-Pro can use phased genotype data to build allele-specific contact maps. We applied HiC-Pro to different Hi-C datasets, demonstrating its ability to easily process large data in a reasonable time. Source code and documentation are available at http://github.com/nservant/HiC-Pro .
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http://dx.doi.org/10.1186/s13059-015-0831-x | DOI Listing |
Nat Commun
January 2025
Bernstein Center for Computational Neuroscience Berlin, Humboldt-Universität zu Berlin, Berlin, Germany.
Understanding vibrissal transduction has advanced by serial sectioning and identified afferent recordings, but afferent mapping onto the complex, encapsulated follicle remains unclear. Here, we reveal male rat C2 vibrissa follicle innervation through synchrotron X-ray phase contrast tomograms. Morphological analysis identified 5% superficial, ~32 % unmyelinated and 63% myelinated deep vibrissal nerve axons.
View Article and Find Full Text PDFSci Technol Adv Mater
November 2024
Faculty of Materials Science and Engineering, Kyoto Institute of Technology, Kyoto, Japan.
We introduce our proprietary Materials Informatics (MI) technologies and our chemistry-oriented methodology for exploring new inorganic functional materials. Using machine learning on crystal structure databases, we developed 'Element Reactivity Maps' that displays the presence or the predicted formation probability of compounds for combinations of 80 × 80 × 80 elements. By analysing atomic coordinates with Delaunay tetrahedral decomposition, we established the concept of Delaunay Chemistry.
View Article and Find Full Text PDFJ Proteome Res
January 2025
Institute for Bioinformatics and Medical Informatics (IBMI), University of Tuebingen, Sand 14, 72076 Tubingen, Germany.
Recent improvements in methods and instruments used in mass spectrometry have greatly enhanced the detection of protein post-translational modifications (PTMs). On the computational side, the adoption of open modification search strategies now allows for the identification of a wide variety of PTMs, potentially revealing hundreds to thousands of distinct modifications in biological samples. While the observable part of the proteome is continuously growing, the visualization and interpretation of this vast amount of data in a comprehensive fashion is not yet possible.
View Article and Find Full Text PDFIntrinsically disordered proteins or regions (IDPs or IDRs) exist as ensembles of conformations in the monomeric state and can adopt diverse binding modes, making their experimental and computational characterization challenging. Here, we developed Disobind, a deep-learning method that predicts inter-protein contact maps and interface residues for an IDR and a partner protein, leveraging sequence embeddings from a protein language model. Several current methods, in contrast, provide partner-independent predictions, require the structure of either protein, and/or are limited by the MSA quality.
View Article and Find Full Text PDFNature
January 2025
Department of Neurobiology and Behavior, Cornell University, Ithaca, NY, USA.
Accurate goal-directed behaviour requires the sense of touch to be integrated with information about body position and ongoing motion. Behaviours such as chewing, swallowing and speech critically depend on precise tactile events on a rapidly moving tongue, but neural circuits for dynamic touch-guided tongue control are unknown. Here, using high-speed videography, we examined three-dimensional lingual kinematics as mice drank from a water spout that unexpectedly changed position during licking, requiring re-aiming in response to subtle contact events on the left, centre or right surface of the tongue.
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