imputation

DANCE 2.0: Transforming single-cell analysis from black box to transparent workflow

DANCE 2.0 automates and interprets single-cell preprocessing by recommending optimal pipelines for various tasks, improving performance across six major analyses.

Electrochemically controlled switching of dyes for enhanced super-resolution optical fluctuation imaging (SOFI)

This paper demonstrates electrochemical control of dye switching to enhance SOFI imaging resolution and speed by reducing switching heterogeneity and increasing switching rates.

Deep-Tissue Two-Photon Brain Imaging Enabled by a Tunable Fiber-Optic Dispersive Wave Generator

This paper introduces a tunable fiber-optic dispersive wave generator for deep-tissue two-photon imaging in mouse brains, achieving high-resolution imaging at depths over 450 micrometers.

Multi-spectral optoacoustic microscopy driven by gas-filled hollow-core fiber laser pulses

This paper develops a gas-filled hollow-core fiber laser source for multi-spectral optoacoustic microscopy, enabling high-resolution label-free bio-imaging across infrared and ultraviolet ranges.

Fast, Bright and Reversible Rhodamine Tags for Live-Cell Imaging

This paper introduces Rho-tag and SiR-tag, fast, reversible, and fluorogenic protein tags for live-cell imaging, compatible with super-resolution techniques and demonstrated in zebrafish larvae.

Denoising 7T Structural MRI with Conditional Generative Diffusion Models

This paper introduces a conditional diffusion model to denoise 7T MRI scans, improving image quality and outperforming existing methods.

SNAP-tag2: faster and brighter protein labeling

This paper introduces SNAP-tag2, an improved version of SNAP-tag with faster labeling kinetics and higher fluorescence brightness for better live-cell imaging.

Enhanced Ultrasound Image Formation with Computationally Efficient Cross-Angular Delay Multiply and Sum Beamforming

This paper introduces a new ultrasound beamforming algorithm that improves image contrast and resolution while maintaining computational efficiency.

GatorST: A Versatile Contrastive Meta-Learning Framework for Spatial Transcriptomic Data Analysis

GatorST improves spatial transcriptomic analysis by integrating graph-based modeling, pseudo-labeling, and contrastive meta-learning to enhance spatial domain identification and downstream tasks.

Fabry-Perot Microscopy for Improved Contrast Enhancement and 3D Cellular Imaging

This paper introduces Fabry-Perot Microscopy (FPM), a label-free technique that enhances contrast and enables 3D imaging of transparent biological samples with up to 20-fold improvement over conventional wide-field microscopy.

A General Strategy to Endow Dyes with Genic Fluorescence for Wash-Free Imaging of Proteins in Living Cells

This paper introduces a method to enhance fluorescent dye imaging in living cells by using FRET pairs to reduce background noise and improve signal-to-noise ratio.

Biologically Informative NA Deconvolution (BIND) excavates hidden features of the proteome from missing values in large-scale datasets

BIND identifies biological significance of missing values in proteomics data, improving analysis and biomarker discovery.

Multiplexed Brain and Visceral Two-Photon Imaging Using a Simulation-Guided Ultrafast Three-Color Fiber Laser

This paper introduces a three-color ultrafast fiber laser platform for multiplexed two-photon imaging, validated in mouse tissue to visualize multiple cellular structures.

Vispro improves imaging analysis for Visium spatial transcriptomics

Vispro improves imaging analysis for Visium spatial transcriptomics by automating image processing tasks and enhancing downstream analysis performance.

FLUID-CELL: Flow-enabled Light and Ultrastructural Imaging Device for Correlative Electron and Light Localization

The paper introduces a microfluidic device that enables correlative fluorescence light microscopy and cryo-electron microscopy for real-time and ultrastructural analysis of cells.

DiffusionST: A deep generative diffusion model-based framework for enhancing spatial transcriptomics data quality and identifying spatial domains

DiffusionST improves spatial transcriptomics data quality and identifies spatial domains through a diffusion model and graph convolutional network.

A large-scale foundation model for bulk transcriptomes

This paper introduces BulkFormer, a foundation model for bulk transcriptome analysis that outperforms existing models in six downstream tasks.

The Art of Not Knowing: Accommodating Structured Missingness in Biomedical Research

This paper addresses structured missingness in biomedical data by introducing a hierarchical imputation framework and advocating for alternative evaluation metrics.

DuReS: An R package for denoising experimental tandem mass spectrometry-based metabolomics data

DuReS improves metabolomics data by removing noise while preserving significant peaks, enhancing spectral matching and reducing false positives.

HD2Net: A Deep Learning Framework for Simultaneous Denoising and Deaberration in Fluorescence Microscopy

HD2Net improves fluorescence microscopy image quality by simultaneously denoising and correcting aberrations without additional hardware, outperforming existing methods in resolution and contrast.

Reduction of SEM charging artefacts in native cryogenic biological samples.

This paper reduces SEM charging artefacts in cryogenic biological samples using interleaved scanning, enabling clearer visualization of previously masked structures.

FM3VCF: A Software Library for Accelerating the Loading of Large VCF Files in Genotype Data Analyses

FM3VCF accelerates loading large VCF files in genotype data analyses by using multiple CPU threads, outperforming existing tools in speed.

A Set of Novel Far-Red Fluorescent Proteins for Temporal Domain Multiplexing and Super-Resolution Imaging

The paper introduces novel far-red fluorescent proteins for temporal domain multiplexing and super-resolution imaging, enabling subcellular structure distinction without hardware modifications.

scMODAL: A general deep learning framework for comprehensive single-cell multi-omics data alignment with feature links

scMODAL is a deep learning framework for aligning single-cell multi-omics data using feature links, effectively removing unwanted variation and identifying cell subpopulations.

Super-resolution imaging in whole cells and tissues via DNA-PAINT on a spinning disk confocal with optical photon reassignment

This paper introduces a DNA-PAINT system with optical photon reassignment on a spinning disk confocal to achieve high-resolution imaging in thick samples and large fields of view.

Augmented Doubly Robust Post-Imputation Inference for Proteomic data

The paper introduces a statistical framework for proteomic data analysis that combines imputation with debiasing to improve inference and reduce false positives in both single-cell and bulk data.

Wideband Tuning and Deep-Tissue Spectral Detection of Indium Phosphide Nano-Laser Particles

This paper develops indium phosphide nanodisk laser particles capable of wideband tuning and deep-tissue spectral detection.

Integrating Alternative Fragmentation Techniques into Standard LC-MS Workflows Using a Single Deep Learning Model Enhances Proteome Coverage

The paper develops a deep learning model that integrates multiple fragmentation techniques into standard LC-MS workflows, improving proteome coverage and identification rates.

Improved quantitation in data-independent acquisition proteomics via retention time boundary imputation

This paper introduces a method to improve quantitation in DIA proteomics by imputing peptide retention time boundaries, leading to more accurate quantifications and better estimation of radiation exposure.

scHiCSRS: A Self-Representation Smoothing Method with Gaussian Mixture Model for Imputing single-cell Hi-C Data

scHiCSRS improves scHi-C data quality by distinguishing structural zeros from dropouts, leading to more accurate clustering in downstream analysis.