![Loading...](https://link.springer.com/static/c4a417b97a76cc2980e3c25e2271af3129e08bbe/images/pdf-preview/spacer.gif)
-
Article
Open AccessscHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis
Spatial transcriptomics has transformed our ability to study tissue complexity. However, it remains challenging to accurately dissect tissue organization at single-cell resolution. Here we introduce scHolograp...
-
Article
Open AccessQuantitative analysis of transcriptome dynamics provides novel insights into developmental state transitions
During embryogenesis, the developmental potential of initially pluripotent cells becomes progressively restricted as they transit to lineage restricted states. The pluripotent cells of Xenopus blastula-stage embr...
-
Article
Open AccessGeneSurrounder: network-based identification of disease genes in expression data
A key challenge of identifying disease–associated genes is analyzing transcriptomic data in the context of regulatory networks that control cellular processes in order to capture multi-gene interactions and yi...
-
Article
Open AccessTime-lagged Ordered Lasso for network inference
Accurate gene regulatory networks can be used to explain the emergence of different phenotypes, disease mechanisms, and other biological functions. Many methods have been proposed to infer networks from gene e...
-
Article
Open AccessPartition decoupling for multi-gene analysis of gene expression profiling data
Multi-gene interactions likely play an important role in the development of complex phenotypes, and relationships between interacting genes pose a challenging statistical problem in microarray analysis, since ...
-
Article
Open AccessIdentifying differential correlation in gene/pathway combinations
An important emerging trend in the analysis of microarray data is to incorporate known pathway information a priori. Expression level "summaries" for pathways, obtained from the expression data for the genes c...