Multiscale Graph Correlation, an interpretable hypothesis test with strong theoretical guarantees for discerning relationships in complex data, requires about half the sample size as other methods, whilst maintaining computational tractability.
CaImAn is an open-software package that equips the neuroscience community with a set of turnkey, fast and scalable solutions to pre-processing problems arising in single cell calcium imaging data analysis.
FLEXIQuant-LF provides the framework to enable large-scale identification of differentially modified peptides and quantification of their modification extent in label-free mass spectrometry data without prior knowledge of the modification type.
Human mobility drives malaria importation within countries and threatens elimination interventions, but can be measured using new approaches that combine parasite genetics, mobile phone data, travel surveys and models.
A comprehensive package for pedigree-based risk modeling, with a highly optimized computational back-end, extends existing models beyond syndrome-specific approaches and incorporates data from panel studies by allowing for an arbitrary number of gene and syndrome associations.
Single cell expression data can be used to determine how regulatory transcription factors and target genes are connected, and is especially useful when studying transcription factors controlling heterogeneous cell states.
A computational strategy for extracting representative numerical features from 3D microscopy data enables in-depth quantitative analysis of cell and tissue organization through machine learning-driven data integration and context-guided visualization.