A5023728748- Bioinformatics and Genomic Networks
- Gene expression and cancer classification
- Single-cell and spatial transcriptomics
- Gene Regulatory Network Analysis
- Computational Drug Discovery Methods
- Rough Sets and Fuzzy Logic
- Cell Image Analysis Techniques
- Immunotherapy and Immune Responses
- Artificial Immune Systems Applications
- Cancer-related molecular mechanisms research
- Advanced Computational Techniques and Applications
- Genomics and Chromatin Dynamics
- Advanced Algorithms and Applications
- Ferroptosis and cancer prognosis
- Advanced Decision-Making Techniques
- RNA Research and Splicing
- Immune cells in cancer
- Advanced Image Processing Techniques
- Image and Signal Denoising Methods
- Pluripotent Stem Cells Research
- DNA Repair Mechanisms
- Genetic Mapping and Diversity in Plants and Animals
- Immune Cell Function and Interaction
- Cancer, Lipids, and Metabolism
- Cell death mechanisms and regulation
University of Chinese Academy of Sciences
2017-2025
Houston Methodist
2024-2025
Chinese Academy of Sciences
2015-2024
Beijing Institute of Genomics
2016-2024
Institute for Advanced Study
2024
Guangdong Polytechnic of Science and Technology
2021-2024
Center for Excellence in Molecular Cell Science
2016-2022
Shanghai Institutes for Biological Sciences
2016-2020
Wuhan University of Technology
2020
Huawei Technologies (China)
2019
Abstract Spatially resolved transcriptomics (SRT) has emerged as a transformative technology for elucidating cellular organization and tissue architecture. However, significant challenge remains in identifying pathology‐relevant spatial functional landscapes within the microenvironment, primarily due to limited integration of cell–cell communication dynamics. To address this limitation, SpaDCN, Spa tially D ynamic graph C onvolutional N etwork framework is proposed, which aligns...
Synthetic lethality through combinatorial targeting DNA damage response (DDR) pathways provides exciting anticancer therapeutic benefit. Currently, the long noncoding RNAs (lncRNAs) have been implicated in tumor drug resistance; however, their potential significance DDR is still largely unknown. Here, we report that a human lncRNA, CTD-2256P15.2, encodes micropeptide, named PAR-amplifying and CtIP-maintaining micropeptide (PACMP), with dual function to maintain CtIP abundance promote...
Cancer immunotherapy using immune checkpoint blockade (ICB) has revolutionized cancer treatment. However, patients with multiple myeloma (MM) rarely respond to ICB. Accumulating evidence indicates that the complicated tumor microenvironment (TME) significantly impacts efficacy of ICB therapy. Therefore, investigating how TME components in MM influence treatment is urgent.
Integrating different omics profiles is a challenging task, which provides comprehensive way to understand complex diseases in multi-view manner. One key for such an integration extract intrinsic patterns concordance with data structures, so as discover consistent information across various types even noise pollution. Thus, we proposed novel framework called 'pattern fusion analysis' (PFA), performs automated alignment and bias correction, fuse local sample-patterns (e.g. from each type)...
TMCO1 (transmembrane and coiled-coil domains 1) is an endoplasmic reticulum (ER) transmembrane protein that actively prevents Ca2+ stores from overfilling. To characterize its physiological function(s), we generated Tmco1-/- knockout (KO) mice. In addition to the main clinical features of human cerebrofaciothoracic (CFT) dysplasia spectrum, females manifest gradual loss ovarian follicles, impaired follicle development, subfertility with a phenotype analogous premature failure (POF) in women....
Recent advances in spatially resolved transcriptomics (SRT) have brought ever-increasing opportunities to characterize expression landscape the context of tissue spatiality. Nevertheless, there still exist multiple challenges accurately detect spatial functional regions tissue. Here, we present a novel contrastive learning framework, SPAtially Contrastive variational AutoEncoder (SpaCAE), which contrasts transcriptomic signals each spot and its neighbors achieve fine-grained structures...
The integration of multi-omics data makes it possible to understand complex biological organisms at the system level. Numerous approaches have been developed by assuming a common underlying space. Due noise and heterogeneity data, performance these is greatly affected. In this work, we propose novel deep neural network architecture, named Deep Latent Space Fusion (DLSF), which integrates learning consistent manifold in sample latent space for disease subtypes identification. DLSF built upon...
Spatial transcriptomics techniques, while measuring gene expression, retain spatial location information, aiding in situ studies of organismal tissue architecture and the progression pathological processes. These techniques generate vast amounts omics data, necessitating development computational methods to reveal underlying microenvironment heterogeneity. The main directions data analysis are domain detection deconvolution, which can identify functional regions parse distribution cell types...
Abstract Spatially resolved transcriptomics (SRT) has emerged as a powerful tool for investigating gene expression in spatial contexts, providing insights into the molecular mechanisms underlying organ development and disease pathology. However, sparsity poses computational challenge to integrate other modalities (e.g. histological images locations) that are simultaneously captured SRT datasets clustering variation analyses. In this study, meet such challenge, we propose multi-modal domain...
Abstract Multiple myeloma (MM) is a hematologic malignancy characterized by uncontrolled proliferation of plasma cells in the bone marrow. MM patients with aggressive progression have poor survival, emphasizing urgent need for identifying new therapeutic targets. Here, we show that leukocyte immunoglobulin-like receptor B1 (LILRB1), transmembrane conducting negative immune response, top-ranked gene associated prognosis patients. LILRB1 deficiency inhibits vivo enhancing ferroptosis cells....
Spatially resolved transcriptomics (SRT) has emerged as a powerful technique for mapping gene expression landscapes within spatial contexts. However, significant challenges persist in effectively integrating with information to elucidate the heterogeneity of biological tissues. Here, we present informed Graph Transformers framework, SpaGT, which leverages both node and edge channels model spatially aware graph representation denoising identifying domains. Unlike conventional neural networks,...
Spatially resolved transcriptomics (SRT) enable the comprehensive characterization of transcriptomic profiles in context tissue microenvironments. Unveiling spatial transcriptional heterogeneity needs to effectively incorporate information accounting for substantial correlation expression measurements. Here, we develop a computational method, SpaSRL (spatially aware self-representation learning), which flexibly enhances and decodes signals simultaneously achieve domain detection functional...
Transcription cofactor vestigial-like 3 (VGLL3), as a master regulator of female-biased autoimmunity, also functions in tumor development, while the underlying mechanisms remain largely elusive. Here, we report that VGLL3 plays an important role DNA damage response (DDR). can be recruited to sites PARylation-dependent manner. depletion impairs accumulation RNF8 and RAD51 at damage, leading reduced homologous recombination efficiency increased cellular sensitivity chemotherapeutic drugs....
Targeted immunotherapy with monoclonal antibodies (mAbs) is an effective and safe method for the treatment of malignancies. Development mAbs improved cytotoxicity, targeting new known tumor-associated antigens, therefore continues to be active research area. We reported that Dickkopf-1 (DKK1) a good target human cancers based on its wide expression in different but not normal tissues. As DKK1 secreted protein, binding directly have limited effects cancer cells vivo. The specificity...
Spatially Resolved Transcriptomics (SRT) offers unprecedented opportunities to elucidate the cellular arrangements within tissues. Nevertheless, absence of deconvolution methods that simultaneously model multi-modal features has impeded progress in understanding heterogeneity spatial contexts. To address this issue, SpaDA is developed, a novel spatially aware domain adaptation method integrates data (i.e., transcriptomics, histological images, and locations) from SRT accurately estimate...
Integration of distinct biological data types could provide a comprehensive view processes or complex diseases. The combinations molecules responsible for different phenotypes form multiple embedded (expression) subspaces, thus identifying the intrinsic structure is challenging by regular integration methods. In this paper, we propose novel framework "Multi-view Subspace Clustering Analysis (MSCA)," which measure local similarities samples in same subspace and obtain global consensus sample...
Abstract Spatially resolved transcriptomics (SRT) technologies facilitate the exploration of cell fates or states within tissue microenvironments. Despite these advances, field has not adequately addressed regulatory heterogeneity influenced by microenvironmental factors. Here, we propose a novel Aligned Graph Transfer Learning (SpaGTL), pretrained on large-scale multi-modal SRT data about 100 million cells/spots to enable inference context-specific spatial gene networks across multiple...
A major challenge of bioinformatics in the era precision medicine is to identify molecular biomarkers for complex diseases. It a general expectation that these or signatures have not only strong discrimination ability, but also readable interpretations biological sense. Generally, conventional expression-based network-based methods mainly capture differential genes networks as biomarkers, however, such focus on phenotypic and usually less functional interpretation. Meanwhile, function-based...
Significantly increasing crop yield is a major and worldwide challenge for food supply security. It well-known that rice cultivated at Taoyuan in Yunnan of China can produce the highest worldwide. Yet, gene regulatory mechanism underpinning this ultrahigh has been mystery. Here, we systematically collected transcriptome data seven key tissues different developmental stages using both as case group another regular planting place Jinghong control group. We identified top 24 candidate...
The generation of ectoderm, mesoderm, and endoderm layers is the most critical biological process during gastrulation embryo development. Such a differentiation in human embryonic stem cells (hESCs) an inherently nonlinear multi-stage dynamical which contain multiple tipping points playing crucial roles cell-fate decision. However, are largely unknown, letting alone understanding molecular regulation on these events. Here by designing module-based dynamic network biomarker (M-DNB) model, we...
Single-cell RNA-sequencing (scRNA-seq) techniques provide unprecedented opportunities to investigate phenotypic and molecular heterogeneity in complex biological systems. However, profiling massive amounts of cells brings great computational challenges accurately efficiently characterize diverse cell populations. Single discriminant analysis (scDA) solves this problem by simultaneously identifying groups metagenes based on the construction cell-by-cell representation graph, then using them...