A5064240230- Cancer-related Molecular Pathways
- Cancer Genomics and Diagnostics
- Cancer Immunotherapy and Biomarkers
- Pancreatic and Hepatic Oncology Research
- Colorectal Cancer Treatments and Studies
- Ocular Oncology and Treatments
- Epigenetics and DNA Methylation
- Immunotherapy and Immune Responses
- HIV Research and Treatment
- Gene expression and cancer classification
- Genomic variations and chromosomal abnormalities
- Cancer-related gene regulation
- Immunodeficiency and Autoimmune Disorders
- Bioinformatics and Genomic Networks
- Single-cell and spatial transcriptomics
- Machine Learning in Bioinformatics
- Advanced biosensing and bioanalysis techniques
- Cell Image Analysis Techniques
- Virus-based gene therapy research
- Hip disorders and treatments
- Bone and Joint Diseases
- Hedgehog Signaling Pathway Studies
- Chromatin Remodeling and Cancer
- RNA modifications and cancer
- Protist diversity and phylogeny
Princess Margaret Cancer Centre
2020-2024
University Health Network
2020-2024
University of Toronto
2023
Chinese Academy of Medical Sciences & Peking Union Medical College
2012-2023
Guang’anmen Hospital
2020-2023
University of Saskatchewan
2016-2021
China Medical University
2019
Jinan University
2017
Merck & Co., Inc., Rahway, NJ, USA (United States)
2011
University of South Florida
2005-2010
With the advances in high-throughput technologies, millions of somatic mutations have been reported past decade. Identifying driver genes with oncogenic from these data is a critical and challenging problem. Many computational methods proposed to predict genes. Among them, machine learning-based usually train classifier representations that concatenate various types features extracted different kinds data. Although successful, simply concatenating may not be best way fuse We notice few...
People with Li-Fraumeni syndrome (LFS) harbor a germline pathogenic variant in the TP53 tumor suppressor gene, face near 100% lifetime risk of cancer, and routinely undergo intensive surveillance protocols. Liquid biopsy has become an attractive tool for range clinical applications, including early cancer detection. Here, we provide proof-of-principle multimodal liquid assay that integrates targeted gene panel, shallow whole-genome, cell-free methylated DNA immunoprecipitation sequencing...
Survey/review study Network Learning for Biomarker Discovery Yulian Ding 1, Minghan Fu Ping Luo 2, and Fang-Xiang Wu 1,3,4,* 1 Division of Biomedical Engineering, University Saskatchewan, S7N 5A9, Saskatoon, Canada 2 Princess Margaret Cancer Centre, Health Network, Toronto, ON M5G 1L7, 3 Department Computer Sciences, 4 Mechanical * Correspondence: faw341@mail.usask.ca Received: 14 October 2022 Accepted: 5 December Published: 27 March 2023 Abstract: Everything is connected thus networks are...
Abstract Early kinetics of circulating tumor DNA (ctDNA) in plasma predict response to pembrolizumab but typically requires sequencing matched tissue or fixed gene panels. We analyzed genome-wide methylation and fragment-length profiles using cell-free methylated immunoprecipitation (cfMeDIP-seq) 204 samples from 87 patients before during treatment with a pan-cancer phase II investigator-initiated trial (INSPIRE). trained signature independent array data The Cancer Genome Atlas quantify...
Computationally predicting disease genes helps scientists optimize the in-depth experimental validation and accelerates identification of real disease-associated genes. Modern high-throughput technologies have generated a vast amount omics data, integrating them is expected to improve accuracy computational prediction. As an integrative model, multimodal deep belief net (DBN) can capture cross-modality features from heterogeneous datasets model complex system. Studies shown its power in...
Disease gene prediction is a challenging task that has variety of applications such as early diagnosis and drug development. The existing machine learning methods suffer from the imbalanced sample issue because number known disease genes (positive samples) much less than unknown which are typically considered to be negative samples. In addition, most have not utilized clinical data patients with specific predict genes. this study, we propose algorithm (called dgSeq) by combining...
Abstract The role of the immune microenvironment in maintaining disease remission patients with multiple myeloma (MM) is not well understood. In this study, we comprehensively profile system newly diagnosed MM receiving continuous lenalidomide maintenance therapy aim discovering correlates long-term treatment response. Leveraging single-cell RNA sequencing and T cell receptor β peripheral blood CyTOF mass cytometry bone marrow, longitudinally characterize landscape 23 before one year after...
Germline pathogenic TP53 variants predispose individuals to a high lifetime risk of developing multiple cancers and are the hallmark feature Li-Fraumeni syndrome (LFS). Our group has previously shown that LFS patients harbor shorter plasma cell-free DNA fragmentation; independent cancer status. To understand functional underpinning cfDNA fragmentation in LFS, we conducted fragmentomic analysis 199 samples from 82 mutation carriers 30 healthy TP53-wildtype controls. We find exhibit an...
Abstract Background Although structural and functional changes of the striatum hippocampus are present in familial Alzheimer’s disease, little is known about effects specific gene mutation or disease progression on their related neural circuits. This study was to evaluate pathogenic striatum- hippocampus-related circuits, including frontostriatal hippocampus-posterior cingulate cortex (PCC) pathways. Methods A total 102 healthy non-carriers, 40 presymptomatic carriers (PMC), 30 symptomatic...
CReSCENT: CanceR Single Cell ExpressioN Toolkit (https://crescent.cloud), is an intuitive and scalable web portal incorporating a containerized pipeline execution engine for standardized analysis of single-cell RNA sequencing (scRNA-seq) data. While scRNA-seq data tumour specimens are readily generated, subsequent requires high-performance computing infrastructure user expertise to build pipelines tailor interpretation cancer biology. CReSCENT uses public sets preconfigured that accessible...
Uveal melanomas are rare tumors arising from melanocytes that reside in the eye. Despite surgical or radiation treatment, approximately 50% of patients with uveal melanoma will progress to metastatic disease, most often liver. Cell-free DNA (cfDNA) sequencing is a promising technology due minimally invasive sample collection and ability infer multiple aspects tumor response. We analyzed 46 serial cfDNA samples 11 over 1-year period following enucleation brachytherapy (n = ∼4/patient) using...
Complex diseases are known to be associated with disease genes. Uncovering disease-gene associations is critical for diagnosis, treatment, and prevention of diseases. Computational algorithms which effectively predict candidate prior experimental proof can greatly reduce the cost time. Most existing methods disease-specific only genes a specific at Similarities among not used during prediction. Meanwhile, most new based on associations, making them unable without genes.In this study,...
To predict the progression of femoral head collapse in Association Research Circulation Osseous (ARCO) Stage 2-3A osteonecrosis based on initial bone resorption lesion.A retrospective analysis location, attenuation, and maximum area coronal position (MAC) lesion ARCO 2 3A was conducted 85 cases (ONFH). The were divided into rapid slow groups according to whether at follow-up greater than mm. characteristics between two compared by variance. Receiver operating characteristic curve used...
Li-Fraumeni syndrome (LFS) is an autosomal dominant cancer-predisposition disorder. Approximately 70% of individuals who fit the clinical definition LFS harbor a pathogenic germline variant in TP53 tumor suppressor gene. However, remaining 30% patients lack and even among carriers, approximately 20% remain cancer-free. Understanding variable cancer penetrance phenotypic variability critical to developing rational approaches accurate, early detection risk-reduction strategies. We leveraged...
ABSTRACT Background Hepatocellular carcinoma (HCC) is one of the most common and lethal malignancies worldwide. HCC diagnosis, monitoring, treatment decisions rely predominantly on imaging. Curative surgery limited to those with disease confined liver, but recurrence common. Detection by mutational profiling blood plasma cell-free DNA (cfDNA) heterogeneity difficulty obtaining tumor tissue guide targeted gene panels. In contrast, methylation patterns reveal biological processes without need...
Ensemble learning with output from multiple supervised and unsupervised models aims to improve the classification accuracy of model ensemble by jointly considering grouping results models. In this paper we cast task as an unconstrained probabilistic embedding problem. Specifically, assume both objects classes/clusters have latent coordinates without constraints in a D-dimensional Euclidean space, consider mapping embedded space into generative process. The prediction object is then...
We created a cross-species display system that allows the of same antibody libraries on both prokaryotic phage and eukaryotic yeast without need for molecular cloning. Using this cross-display system, large, diverse library can be constructed once subsequently used selection in systems. In article, we performed parallel an maturation using platform. This allowed us to isolate more unique hits than single-species selection, with 162 clones from 107 yeast. addition, were able shuttle back...
The identification of disease genes is an essential issue to decipher the mechanisms complex diseases. Many existing methods combine machine learning algorithms and network information predict are based on `guilt by association' assumption, where considered be close each other in a biomolecular network. Although these have gained many novel findings, most them ignored edge dynamic changes networks under different conditions when only utilizing principle, which will limit their performance....
Abstract Background With the development of technology single-cell sequence, revealing homogeneity and heterogeneity between cells has become a new area computational systems biology research. However, clustering cell types becomes more complex with mutual penetration different instability gene expression. One way overcoming this problem is to group similar, related single together by means various analysis methods. Although some methods such as spectral can do well in identification types,...
Summary Despite advances in cancer therapeutics, early detection is often the best prognostic indicator for survival ( 1 ). People with Li-Fraumeni syndrome harbor a germline pathogenic variant tumor suppressor gene TP53 2 ) and face near 100% lifetime risk of developing wide spectrum of, multiple, cancers 3 mutation carriers routinely undergo intensive surveillance protocols which, although associated significantly improved survival, are burdensome to both patient health care system 4...
Single-cell RNA sequencing (scRNA-seq) clustering and labelling methods are used to determine precise cellular composition of tissue samples. Automated rely on either unsupervised, cluster-based approaches or supervised, cell-based identify cell types. The high complexity cancer poses a unique challenge, as tumor microenvironments often composed diverse subpopulations with functional effects that may lead disease progression, metastasis treatment resistance. Here, we assess 17 9 scRNA-seq...
Abstract Cellular functions are always performed by protein complexes. At present, many approaches have been proposed to identify complexes from protein–protein interaction (PPI) networks. Some focus on detecting local dense subgraphs in PPI networks which regarded as protein‐complex cores, then including neighbors. However, gene expression profiles at different time points or tissues it is known that proteins dynamic. Therefore, identifying dynamic should become very important and...