[HTML][HTML] Next-generation machine learning for biological networks
Machine learning, a collection of data-analytical techniques aimed at building predictive
models from multi-dimensional datasets, is becoming integral to modern biological research …
models from multi-dimensional datasets, is becoming integral to modern biological research …
Machine learning bridges omics sciences and plant breeding
J Yan, X Wang - Trends in Plant Science, 2023 - cell.com
Some of the biological knowledge obtained from fundamental research will be implemented
in applied plant breeding. To bridge basic research and breeding practice, machine learning …
in applied plant breeding. To bridge basic research and breeding practice, machine learning …
Benchmarking algorithms for gene regulatory network inference from single-cell transcriptomic data
We present a systematic evaluation of state-of-the-art algorithms for inferring gene
regulatory networks from single-cell transcriptional data. As the ground truth for assessing …
regulatory networks from single-cell transcriptional data. As the ground truth for assessing …
Integrative analysis identifies four molecular and clinical subsets in uveal melanoma
AG Robertson, J Shih, C Yau, EA Gibb, J Oba… - Cancer cell, 2017 - cell.com
Comprehensive multiplatform analysis of 80 uveal melanomas (UM) identifies four
molecularly distinct, clinically relevant subtypes: two associated with poor-prognosis …
molecularly distinct, clinically relevant subtypes: two associated with poor-prognosis …
Integrative bulk and single-cell profiling of premanufacture T-cell populations reveals factors mediating long-term persistence of CAR T-cell therapy
The adoptive transfer of chimeric antigen receptor (CAR) T cells represents a breakthrough
in clinical oncology, yet both between-and within-patient differences in autologously derived …
in clinical oncology, yet both between-and within-patient differences in autologously derived …
Gene regulatory network inference from single-cell data using multivariate information measures
While single-cell gene expression experiments present new challenges for data processing,
the cell-to-cell variability observed also reveals statistical relationships that can be used by …
the cell-to-cell variability observed also reveals statistical relationships that can be used by …
A comprehensive survey of regulatory network inference methods using single cell RNA sequencing data
Gene regulatory network is a complicated set of interactions between genetic materials,
which dictates how cells develop in living organisms and react to their surrounding …
which dictates how cells develop in living organisms and react to their surrounding …
The integrated genomic landscape of thymic epithelial tumors
Thymic epithelial tumors (TETs) are one of the rarest adult malignancies. Among TETs,
thymoma is the most predominant, characterized by a unique association with autoimmune …
thymoma is the most predominant, characterized by a unique association with autoimmune …
Network approaches to systems biology analysis of complex disease: integrative methods for multi-omics data
In the past decade, significant progress has been made in complex disease research across
multiple omics layers from genome, transcriptome and proteome to metabolome. There is an …
multiple omics layers from genome, transcriptome and proteome to metabolome. There is an …
[HTML][HTML] Single-cell transcriptomics reveals that differentiation and spatial signatures shape epidermal and hair follicle heterogeneity
The murine epidermis with its hair follicles represents an invaluable model system for tissue
regeneration and stem cell research. Here we used single-cell RNA-sequencing to reveal …
regeneration and stem cell research. Here we used single-cell RNA-sequencing to reveal …