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Defining cell identity is a fundamental task in dissecting the cellular heterogeneity in single-cell data. Here the authors developed Cepo, a method to uncover cell identity genes and enhance the retrieval of cellular identities from scRNA-seq data.
The authors show that accurate bootstrap confidence limits on inferred evolutionary relationships of species can be estimated by bootstrapping a collection of little samples of very long sequence alignments. Little bootstraps take a fraction of computer time and memory compared to the standard bootstrap, enabling big data analytics on personal computers.
Massimino et al. propose the Inflammatory Bowel Disease Transcriptome and Metatranscriptome Meta-Analysis (IBD TaMMA) framework, an open-source platform for expediting the investigation of IBD-specific transcriptomics and metatranscriptomics signatures.
A computational approach to predictive modeling of embryonic development is presented and validated by integrating imaging, biochemical and genetic studies of tissue patterning in Drosophila embryogenesis.
Raven is designed to democratize genome assembly, being a simple and efficient tool while keeping high accuracy. Using a method for detection of false overlaps based on graph drawing, it can be employed for various genome sizes.
Sharing of personal genomics data raises privacy concerns due to the sensitive nature of the data. A citizen-centric approach involving cryptographic privacy-preserving technologies and blockchains is proposed to address this problem.
Aligning multimodal data for cell type research is a challenging problem in neuroscience. Coupled autoencoders, a deep neural network-based methodology, can be used to effectively address this task.
Using voice-based technologies, ChemVox is able to answer quantum chemistry questions in seconds, thus making such complex questions more accessible to the community.
