A5100702956- Microbial Community Ecology and Physiology
- Genomics and Phylogenetic Studies
- Bioinformatics and Genomic Networks
- Microbial Metabolic Engineering and Bioproduction
- Single-cell and spatial transcriptomics
- Natural product bioactivities and synthesis
- Gene expression and cancer classification
- Pharmaceutical and Antibiotic Environmental Impacts
- Machine Learning in Bioinformatics
- Metaheuristic Optimization Algorithms Research
- Gene Regulatory Network Analysis
- Phytochemical compounds biological activities
- Microplastics and Plastic Pollution
- Gut microbiota and health
- Effects and risks of endocrine disrupting chemicals
- Cancer Genomics and Diagnostics
- Genomics and Rare Diseases
- Composting and Vermicomposting Techniques
- Bacterial Genetics and Biotechnology
- Synthesis of Organic Compounds
- Evolutionary Algorithms and Applications
- Advanced Multi-Objective Optimization Algorithms
- Biofuel production and bioconversion
- Soil Carbon and Nitrogen Dynamics
- RNA and protein synthesis mechanisms
Harbin Institute of Technology
2019-2024
Ministry of Education of the People's Republic of China
2024
Shanghai East Hospital
2020-2024
Hunan Academy of Agricultural Sciences
2019-2024
Heilongjiang Institute of Technology
2024
Duke Kunshan University
2023
Jilin University
2014-2023
Guangdong Ocean University
2021-2023
University of Auckland
2022-2023
ShanghaiTech University
2023
With the high prevalence of breast cancer, it is urgent to find out intrinsic difference between various subtypes, so as infer underlying mechanisms. Given available multi-omics data, their proper integration can improve accuracy cancer subtype recognition. In this study, DeepMO, a model using deep neural networks based on was employed for classifying subtypes. Three types omics data including mRNA DNA methylation and copy number variation (CNV) were collected from The Cancer Genome Atlas...
Abstract The recently developed single-cell CRISPR screening techniques, independently termed Perturb-Seq, CRISP-seq, or CROP-seq, combine pooled with RNA-seq to investigate functional in a granularity. Here, we present MUSIC, an integrated pipeline for model-based understanding of data. Comprehensive tests applied all the publicly available data revealed that MUSIC accurately quantifies and prioritizes individual gene perturbation effect on cell phenotypes tolerance substantial noise exists...
Abstract Here, we present a multi-modal deep generative model, the single-cell Multi-View Profiler (scMVP), which is designed for handling sequencing data that simultaneously measure gene expression and chromatin accessibility in same cell, including SNARE-seq, sci-CAR, Paired-seq, SHARE-seq, Multiome from 10X Genomics. scMVP generates common latent representations dimensionality reduction, cell clustering, developmental trajectory inference separate imputations differential analysis...
Abstract Understanding ethanol-induced stresses and responses in biofuel-producing bacteria at systems level has significant implications engineering more efficient biofuel producers. We present a computational study of transcriptomic genomic data both ethanol-stressed ethanol-adapted E. coli cells with computationally predicated ethanol-binding proteins experimentally identified ethanol tolerance genes. Our analysis suggests: (1) damages cell wall membrane integrity, causing increased...
Abstract Structural Variants (SVs) are a crucial type of genetic variant that can significantly impact phenotypes. Therefore, the identification SVs is an essential part modern genomic analysis. In this article, we present kled, ultra-fast and sensitive SV caller for long-read sequencing data given specially designed approach with novel signature-merging algorithm, custom refinement strategies high-performance program structure. The evaluation results demonstrate kled achieve optimal calling...
Introduction: As the evaluation indices, cancer grading and subtyping have diverse clinical, pathological, molecular characteristics with prognostic therapeutic implications. Although researchers begun to study differentiation subtype prediction, most of relevant methods are based on traditional machine learning rely single omics data. It is necessary explore a deep algorithm that integrates multi-omics data achieve classification prediction subtypes. Methods: This paper proposes fusion...
Particle swarm optimizations (PSOs) are drawing extensive attention from both research and engineering fields due to their simplicity powerful global search ability. However, there two issues needing be improved: one is that the classical PSO converges slowly; other tends result in premature convergence, especially for multi-modal problems. This paper attempts address these issues. Firstly, improve convergent efficiency, this proposes an asymptotic predicting model of globally-optimal...
Expansion of penguin activity in maritime Antarctica, under ice thaw, increases the chances feces affecting ornithogenic soil microbiomes. The detail such effects was only recently studied so far (Santamans et al, 2017). By comparing geochemistry and microbiome composition (one site) outside (three sites) rookery, we found significant on both. First, change geochemistry, causing increased moisture content soils nutrients C, N, P, Si rookery compared to non-rookery sites, but not pH. Second,...
Abstract Background The precise characterization of individual tumors and immune microenvironments using transcriptome sequencing has provided a great opportunity for successful personalized cancer treatment. However, the treatment response is often characterized by in vitro assays or bulk transcriptomes that neglect heterogeneity malignant vivo microenvironment, motivating need to use single-cell Methods Here, we present comboSC, computational proof-of-concept study explore feasibility...
scLearn is a metric learning-based framework with measurement and threshold learned automatically for single-cell assignment.
Estuaries can act as plastic retention hotspots, but the hydrodynamic controls on are not well understood. This study investigates of river-sourced buoyant plastics in a well-mixed estuary, Waitematā Estuary, using validated numerical simulations floats with different tides, winds, and freshwater discharge. The proportion grounded shore all seven is higher than 60 % over 90 five after ten days. <20 leave estuarine mouth any simulations. An increase two orders magnitude discharge doubles...
Genome-scale metabolic networks (GSMs) are fundamental systems biology representations of a cell's entire set stoichiometrically balanced reactions. However, such static GSMs do not incorporate the functional organization genes and their dynamic regulation (e.g., operons regulons). Specifically, there numerous topologically coupled local reactions through which fluxes coordinated; global growth state often dynamically regulates many gene expression via transcription factor regulators. Here,...
Background. Nonspecific orbital inflammation is a common ophthalmopathy with high prevalence among adult females. Yet, its molecular mechanisms behind are poorly understood. Regulation of gene expression probably plays an important role in this disease. Thus, we utilized coexpression networks to identify key modules and hub genes involved nonspecific inflammation. Methods. Data samples ( <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" id="M1"> <a:mi>n</a:mi> <a:mo>=</a:mo>...
In classical genetic algorithm, fitness evaluations are often very expensive or highly time-consuming, especially for some engineering optimization problems. We present an efficient algorithm (GA) by combining clustering methods with empirical estimating formula. The new individuals clustered at first, and then only the cluster representatives really evaluated its original time-consuming computing processes, other undergo high evaluating processes using To further improve accuracy of...