Deep learning and its applications in biomedicine
Advances in biological and medical technologies have been providing us explosive volumes
of biological and physiological data, such as medical images, electroencephalography, …
of biological and physiological data, such as medical images, electroencephalography, …
[PDF][PDF] clusterProfiler 4.0: A universal enrichment tool for interpreting omics data
…, T Feng, L Zhou, W Tang, LI Zhan, X Fu, S Liu, X Bo… - The innovation, 2021 - cell.com
Functional enrichment analysis is pivotal for interpreting high-throughput omics data in life
science. It is crucial for this type of tool to use the latest annotation databases for as many …
science. It is crucial for this type of tool to use the latest annotation databases for as many …
Machine learning methods, databases and tools for drug combination prediction
…, B Yan, Y Zhang, J Wang, S He, X Bo - Briefings in …, 2022 - academic.oup.com
Combination therapy has shown an obvious efficacy on complex diseases and can greatly
reduce the development of drug resistance. However, even with high-throughput screens, …
reduce the development of drug resistance. However, even with high-throughput screens, …
[HTML][HTML] PEDLA: predicting enhancers with a deep learning-based algorithmic framework
Transcriptional enhancers are non-coding segments of DNA that play a central role in the
spatiotemporal regulation of gene expression programs. However, systematically and …
spatiotemporal regulation of gene expression programs. However, systematically and …
GOSemSim: an R package for measuring semantic similarity among GO terms and gene products
The semantic comparisons of Gene Ontology (GO) annotations provide quantitative ways to
compute similarities between genes and gene groups, and have became important basis for …
compute similarities between genes and gene groups, and have became important basis for …
[HTML][HTML] Deep learning-based transcriptome data classification for drug-target interaction prediction
L Xie, S He, X Song, X Bo, Z Zhang - BMC genomics, 2018 - Springer
… Xiaochen Bo … Xiaochen Bo … Zhongnan Zhang and Xiaochen Bo directed the project
and contributed to manuscript revisions. All Authors read and approved the final manuscript. …
and contributed to manuscript revisions. All Authors read and approved the final manuscript. …
A survey and evaluation of Web-based tools/databases for variant analysis of TCGA data
…, H Li, S Jiang, R Li, W Li, H Chen, X Bo - Briefings in …, 2019 - academic.oup.com
The Cancer Genome Atlas (TCGA) is a publicly funded project that aims to catalog and
discover major cancer-causing genomic alterations with the goal of creating a comprehensive ‘…
discover major cancer-causing genomic alterations with the goal of creating a comprehensive ‘…
[HTML][HTML] Comprehensive identification and annotation of cell type-specific and ubiquitous CTCF-binding sites in the human genome
H Chen, Y Tian, W Shu, X Bo, S Wang - PloS one, 2012 - journals.plos.org
Chromatin insulators are DNA elements that regulate the level of gene expression either by
preventing gene silencing through the maintenance of heterochromatin boundaries or by …
preventing gene silencing through the maintenance of heterochromatin boundaries or by …
ggtreeExtra: compact visualization of richly annotated phylogenetic data
…, L Zhan, T Wu, E Hu, Y Jiang, X Bo… - Molecular biology …, 2021 - academic.oup.com
We present the ggtreeExtra package for visualizing heterogeneous data with a phylogenetic
tree in a circular or rectangular layout ( https://www.bioconductor.org/packages/ggtreeExtra )…
tree in a circular or rectangular layout ( https://www.bioconductor.org/packages/ggtreeExtra )…
[HTML][HTML] A benchmark study of deep learning-based multi-omics data fusion methods for cancer
Background A fused method using a combination of multi-omics data enables a comprehensive
study of complex biological processes and highlights the interrelationship of relevant …
study of complex biological processes and highlights the interrelationship of relevant …