Volume 18 Issue 11, November 2021

Sydney’s beauty, candy-store lollies and a community view of glycoproteomics software.

The exception proves the rule.

Four independent research groups have used proximity ligation techniques to profile the in vivo mouse secretome.

An artificial system models the mechanical properties of the tumor microenvironment in vitro.

Directed evolution of adeno-associated virus capsids with the DELIVER approach generates tissue-specific viruses.

Researchers identified a single-effector Cas, Cas7-11, that architecturally diverges from previous CRISPR single- or multi-component systems and can possess RNA knockdown activity without detectable collateral activity in mammalian cells.

The proliferation of versatile open software and hardware for microscopy is helping to democratize biological imaging for both current and aspiring scientists.

Computational methods use different integrative strategies to tackle the challenges of spatially resolved transcriptomics data analysis.

The MISpheroID knowledgebase records and organizes experimental parameters from thousands of cancer spheroid experiments, revealing heterogeneity and a lack of transparency in key spheroid research reporting practices.

This Perspective discusses how neuroscience can benefit from harnessing nanoscience-based tools for manipulating and recording neuronal activity.

A knowledgebase developed for increased the transparency of reporting in spheroid research.

This analysis presents the results of a community-based evaluation of existing software for large-scale glycopeptide data analysis.

A linearly interpretable framework for analyzing single-cell omics data improves data representation, visualization and structure discovery.

The PEPPER-Margin-DeepVariant pipeline achieves highly accurate variant calling using nanopore and other long-read sequencing data.

The Signac framework enables the end-to-end analysis of single-cell chromatin data and interoperability with the Seurat package for multimodal analysis.

SpaGCN is a spatially resolved transcriptomics data analysis tool for identifying spatial domains and spatially variable genes using graph convolutional networks.

Tangram is a versatile tool for aligning single-cell and single-nucleus RNA-seq data to spatially resolved transcriptomics data using deep learning.

DeepLC, a deep learning-based peptide retention time predictor, can predict retention times for unmodified peptides as well as peptides with previously unseen modifications.

HERMES is a molecular-formula-oriented and peak-detection-free method that uses LC/MS1 information to optimize MS2 acquisition for LC/MS-based metabolomic analysis.

The NetID algorithm annotates untargeted LC-MS metabolomics data by combining known biochemical and metabolomic principles with a global network optimization strategy.

DeepFinder is a deep learning-based tool for identifying macromolecules in cellular cryo-electron tomograms. DeepFinder performs with an accuracy comparable to expert-supervised ground truth annotations on multiple experimental datasets.

DeepCAD is a self-supervised deep-learning approach for denoising calcium imaging data. DeepCAD improved SNR and facilitates neuron extraction and spike inference.

DeepInterpolation is a self-supervised deep learning-based denoising approach for calcium imaging, electrophysiology and fMRI data. The approach increases the signal-to-noise ratio and allows extraction of more information from the processed data than from the raw data.