Hai Fang

Publications

• Function-selective domain architecture plasticity potentials in eukaryotic genome evolution
• Transcriptome and proteome analyses of drug interactions with natural products
• Transcriptome analysis of early organogenesis in human embryos.
• SUPERFAMILY 1.75 including a domain-centric gene ontology method
• A topology-preserving selection and clustering approach to multidimensional biological data.
• dcGO: database of domain-centric ontologies on functions, phenotypes, diseases and more.
• supraHex: An R/Bioconductor package for tabular omics data analysis using a supra-hexagonal map
• The 'dnet' approach promotes emerging research on cancer patient survival
• Preferential eradication of acute myelogenous leukemia stem cells by fenretinide
• dcGOR: an R package for analysing ontologies and protein domain annotations
• XGR software for enhanced interpretation of genomic summary data, illustrated by application to immunological traits.
• Regulatory Genomic Data Cubism
• A genetics-led approach defines the drug target landscape of 30 immune-related traits
• From genome-wide association studies to rational drug target prioritisation in inflammatory arthritis
• A PML/RARα direct target atlas redefines transcriptional deregulation in acute promyelocytic leukemia
• Priority index: database of genetic targets in immune-mediated disease
• A large-scale evaluation of computational protein function prediction
• A promoter-level mammalian expression atlas
• I3: A Self-organising Learning Workflow for Intuitive Integrative Interpretation of Complex Genetic Data
• PiER: web-based facilities tailored for genetic target prioritisation harnessing human disease genetics, functional genomics and protein interactions
• OpenXGR: a web-server update for genomic summary data interpretation
• Priority index for asthma (PIA): In silico discovery of shared and distinct drug targets for adult- and childhood-onset disease
• A domain-centric solution to functional genomics via dcGO Predictor
• Prospective observational study on biomarkers of response in pancreatic ductal adenocarcinoma