Image-based profiling is a maturing strategy by which the rich information present in
biological images is reduced to a multidimensional profile, a collection of extracted image …

As a data-driven science, genomics largely utilizes machine learning to capture
dependencies in data and derive novel biological hypotheses. However, the ability to extract …

Scanpy is a scalable toolkit for analyzing single-cell gene expression data. It includes
methods for preprocessing, visualization, clustering, pseudotime and trajectory inference …

The differentiation of neural stem cells (NSCs) into neurons is proposed to be critical in
devising potential cell-based therapeutic strategies for central nervous system (CNS) …

Single-cell RNA-seq quantifies biological heterogeneity across both discrete cell types and
continuous cell transitions. Partition-based graph abstraction (PAGA) provides an …

Deep learning describes a class of machine learning algorithms that are capable of
combining raw inputs into layers of intermediate features. These algorithms have recently …

These guidelines are a consensus work of a considerable number of members of the
immunology and flow cytometry community. They provide the theory and key practical …

Imaging flow cytometry combines the high-event-rate nature of flow cytometry with the
advantages of single-cell image acquisition associated with microscopy. The measurement …

Deep learning has exploded in the public consciousness, primarily as predictive and
analytical products suffuse our world, in the form of numerous human-centered smart-world …

The recent advent of methods for high-throughput single-cell molecular profiling has
catalyzed a growing sense in the scientific community that the time is ripe to complete the …