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Article
Open AccessFloods and cause-specific mortality in the UK: a nested case-control study
Floods are the most frequent weather-related disaster, causing significant health impacts worldwide. Limited studies have examined the long-term consequences of flooding exposure.
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Article
Health Impacts of Wildfire Smoke on Children and Adolescents: A Systematic Review and Meta-analysis
Wildfire smoke is associated with human health, becoming an increasing public health concern. However, a comprehensive synthesis of the current evidence on the health impacts of ambient wildfire smoke on child...
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Article
Open AccessDiCleave: a deep learning model for predicting human Dicer cleavage sites
MicroRNAs (miRNAs) are a class of non-coding RNAs that play a pivotal role as gene expression regulators. These miRNAs are typically approximately 20 to 25 nucleotides long. The maturation of miRNAs requires D...
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Article
Deep domain adversarial neural network for the deconvolution of cell type mixtures in tissue proteome profiling
Cell type deconvolution is a computational method for the determination/resolution of cell type proportions from bulk sequencing data, and is frequently used for the analysis of divergent cell types in tumour ...
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Article
Open AccessSmad7 in the hippocampus contributes to memory impairment in aged mice after anesthesia and surgery
Postoperative cognitive dysfunction (POCD) is a common neurological complication following anesthesia and surgery. Increasing evidence has demonstrated that neuroinflammation caused by systemic inflammatory re...
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Article
Open AccessGenetic algorithm-based feature selection with manifold learning for cancer classification using microarray data
Microarray data have been widely utilized for cancer classification. The main characteristic of microarray data is “large p and small n” in that data contain a small number of subjects but a large number of ge...
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Article
Open AccessMulti-modality data-driven analysis of diagnosis and treatment of psoriatic arthritis
Psoriatic arthritis (PsA) is associated with psoriasis, featured by its irreversible joint symptoms. Despite the significant impact on the healthcare system, it is still challenging to leverage machine learnin...
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Protocol
Predicting Pseudouridine Sites with Porpoise
is a ubiquitous modification and plays a crucial role in many biological processes. However, it remains a challenging task to identify sites using expensive and time-consuming experimental research. To th...
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Article
Open AccessPreAcrs: a machine learning framework for identifying anti-CRISPR proteins
Anti-CRISPR proteins are potent modulators that inhibit the CRISPR-Cas immunity system and have huge potential in gene editing and gene therapy as a genome-editing tool. Extensive studies have shown that anti-...
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Article
Open AccessCell graph neural networks enable the precise prediction of patient survival in gastric cancer
Gastric cancer is one of the deadliest cancers worldwide. An accurate prognosis is essential for effective clinical assessment and treatment. Spatial patterns in the tumor microenvironment (TME) are conceptual...
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Article
Open AccessA polytherapy based approach to combat antimicrobial resistance using cubosomes
A depleted antimicrobial drug pipeline combined with an increasing prevalence of Gram-negative ‘superbugs’ has increased interest in nano therapies to treat antibiotic resistance. As cubosomes and polymyxins d...
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Protocol
Systematic Characterization of Lysine Post-translational Modification Sites Using MUscADEL
Among various types of protein post-translational modifications (PTMs), lysine PTMs play an important role in regulating a wide range of functions and biological processes. Due to the generation and accumulat...
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Article
PCprophet: a framework for protein complex prediction and differential analysis using proteomic data
Despite the availability of methods for analyzing protein complexes, systematic analysis of complexes under multiple conditions remains challenging. Approaches based on biochemical fractionation of intact, nat...
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Article
Open AccessReCGBM: a gradient boosting-based method for predicting human dicer cleavage sites
Human dicer is an enzyme that cleaves pre-miRNAs into miRNAs. Several models have been developed to predict human dicer cleavage sites, including PHDCleav and LBSizeCleav. Given an input sequence, these models...
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Article
A framework towards data analytics on host–pathogen protein–protein interactions
With the rapid development of high-throughput technologies, systems biology is now embracing a great opportunity made possible by the increased accumulation of data available online. Biological data analytics ...
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Chapter and Conference Paper
PhosTransfer: A Deep Transfer Learning Framework for Kinase-Specific Phosphorylation Site Prediction in Hierarchy
Machine learning algorithms have been widely used for predicting kinase-specific phosphorylation sites. However, the scarcity of training data for specific kinases makes it difficult to train effective models ...
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Article
Open AccessSIMLIN: a bioinformatics tool for prediction of S-sulphenylation in the human proteome based on multi-stage ensemble-learning models
S-sulphenylation is a ubiquitous protein post-translational modification (PTM) where an S-hydroxyl (−SOH) bond is formed via the reversible oxidation on the Sulfhydryl group of cysteine (C). Recent experimenta...
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Article
Open AccessPositive-unlabelled learning of glycosylation sites in the human proteome
As an important type of post-translational modification (PTM), protein glycosylation plays a crucial role in protein stability and protein function. The abundance and ubiquity of protein glycosylation across t...
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Article
Open AccessCharacterization of the Src-regulated kinome identifies SGK1 as a key mediator of Src-induced transformation
Despite significant progress, our understanding of how specific oncogenes transform cells is still limited and likely underestimates the complexity of downstream signalling events. To address this gap, we use ...
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Article
Open AccessPhosContext2vec: a distributed representation of residue-level sequence contexts and its application to general and kinase-specific phosphorylation site prediction
Phosphorylation is the most important type of protein post-translational modification. Accordingly, reliable identification of kinase-mediated phosphorylation has important implications for functional annotati...
