A survey on deep matrix factorizations
Constrained low-rank matrix approximations have been known for decades as powerful
linear dimensionality reduction techniques able to extract the information contained in large …
linear dimensionality reduction techniques able to extract the information contained in large …
The evolution, evolvability and engineering of gene regulatory DNA
Mutations in non-coding regulatory DNA sequences can alter gene expression, organismal
phenotype and fitness,–. Constructing complete fitness landscapes, in which DNA …
phenotype and fitness,–. Constructing complete fitness landscapes, in which DNA …
Map** phenotypic plasticity upon the cancer cell state landscape using manifold learning
Phenotypic plasticity describes the ability of cancer cells to undergo dynamic, nongenetic
cell state changes that amplify cancer heterogeneity to promote metastasis and therapy …
cell state changes that amplify cancer heterogeneity to promote metastasis and therapy …
Non-linear archetypal analysis of single-cell RNA-seq data by deep autoencoders
Advances in single-cell RNA sequencing (scRNA-seq) have led to successes in discovering
novel cell types and understanding cellular heterogeneity among complex cell populations …
novel cell types and understanding cellular heterogeneity among complex cell populations …
K-Deep Simplex: Manifold Learning via Local Dictionaries
We propose-Deep Simplex (KDS) which, given a set of data points, learns a dictionary
comprising synthetic landmarks, along with representation coefficients supported on a …
comprising synthetic landmarks, along with representation coefficients supported on a …
Quantitative comparison of principal component analysis and unsupervised deep learning using variational autoencoders for shape analysis of motile cells
Cell motility is a crucial biological function for many cell types, including the immune cells in
our body that act as first responders to foreign agents. In this work we consider the …
our body that act as first responders to foreign agents. In this work we consider the …
Biarchetype analysis: simultaneous learning of observations and features based on extremes
We introduce a novel exploratory technique, termed biarchetype analysis, which extends
archetype analysis to simultaneously identify archetypes of both observations and features …
archetype analysis to simultaneously identify archetypes of both observations and features …
Map** the gene space at single-cell resolution with gene signal pattern analysis
In single-cell sequencing analysis, several computational methods have been developed to
map the cellular state space, but little has been done to map or create embeddings of the …
map the cellular state space, but little has been done to map or create embeddings of the …
K-deep simplex: Deep manifold learning via local dictionaries
We propose K-Deep Simplex (KDS) which, given a set of data points, learns a dictionary
comprising synthetic landmarks, along with representation coefficients supported on a …
comprising synthetic landmarks, along with representation coefficients supported on a …
A comprehensive fitness landscape model reveals the evolutionary history and future evolvability of eukaryotic cis-regulatory DNA sequences
Mutations in non-coding cis-regulatory DNA sequences can alter gene expression,
organismal phenotype, and fitness. Fitness landscapes, which map DNA sequence to …
organismal phenotype, and fitness. Fitness landscapes, which map DNA sequence to …