GitHub

Sparse InversE Covariance estimation for Ecological Association and Statistical Inference

This package will be useful to anybody who wants to infer graphical models for all sorts of compositional data, though primarily intended for microbiome relative abundance data (generated from 16S ...
IEEE

Flexible Background Modeling for Hyperspectral Anomaly Detection Using Convolutional Sparse Coding

Abstract: This paper proposes a hyperspectral (HS) anomaly detection method using a novel background model based on convolutional sparse coding (CSC). One promising HS anomaly detection approach is to ...
C&EN

The Electronic Structure of the Hydrogen Molecule: A Tutorial Exercise in Classical and Quantum Computation

National Quantum Computing Centre, Rutherford Appleton Laboratory, Harwell Campus, Didcot, Oxfordshire OX11 0QX, U.K. Riverlane, St Andrews House, 59 St Andrews ...
C&EN

Tutorial on In Situ and Operando (Scanning) Transmission Electron Microscopy for Analysis of Nanoscale Structure–Property Relationships

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator.
PNAS

Sparse species interactions reproduce abundance correlation patterns in microbial communities

Microbes—the most abundant organisms on Earth—form complex communities with a profound influence on many problems, from human health to ecosystem management. Understanding species interactions is of ...
Nature

A scalable sparse neural network framework for rare cell type annotation of single-cell transcriptome data

Automatic cell type annotation methods are increasingly used in single-cell RNA sequencing (scRNA-seq) analysis due to their fast and precise advantages. However, current methods often fail to account ...
Frontiers

Replicated Spatial Point Pattern Analyses for Ecological Inference: A Tutorial Using the RSPPlme4 Package in R

The analysis of spatial point patterns has greatly advanced our understanding of ecological processes. However, the methods currently available for analyzing replicated spatial point patterns (RSPPs) ...
Frontiers

Deep-Learning-Based Multivariate Pattern Analysis (dMVPA): A Tutorial and a Toolbox

In recent years, multivariate pattern analysis (MVPA) has been hugely beneficial for cognitive neuroscience by making new experiment designs possible and by increasing the inferential power of ...