A5114406830- Radiomics and Machine Learning in Medical Imaging
- Cancer Genomics and Diagnostics
- Single-cell and spatial transcriptomics
- Wheat and Barley Genetics and Pathology
- Biomedical Text Mining and Ontologies
- Sphingolipid Metabolism and Signaling
- vaccines and immunoinformatics approaches
- Bioinformatics and Genomic Networks
- Insect Resistance and Genetics
- Fungal and yeast genetics research
- Monoclonal and Polyclonal Antibodies Research
- Biomedical and Engineering Education
- Biochemical and Structural Characterization
- Topic Modeling
- Entomopathogenic Microorganisms in Pest Control
- Immunotherapy and Immune Responses
- Immune Response and Inflammation
- Inflammasome and immune disorders
- Science, Research, and Medicine
- Genomics and Phylogenetic Studies
Northeast Normal University
2024
Heilongjiang University of Chinese Medicine
2021
<title>Abstract</title> The utility of deep neural nets has been demonstrated for mapping hematoxylin-and-eosin (H&E) stained image features to expression individual genes. However, these models have not employed discover clinically relevant spatial biomarkers. Here we develop MOSBY (<bold>M</bold>ulti-<bold>Omic</bold> translation whole slide images <bold>S</bold>patial <bold>B</bold>iomarker discover<bold>Y</bold>) that leverages contrastive self-supervised pretraining extract improved...
In biomedical literature, biological pathways are commonly described through a combination of images and text. These contain valuable information, including genes their relationships, which provide insight into mechanisms precision medicine. Curating pathway information across the literature enables integration this to build comprehensive knowledge base. While some studies have extracted from text independently, they often overlook correspondence between two modalities. paper, we present...
Abstract Antigen presentation on MHC Class II (pMHCII presentation) plays an essential role in the adaptive immune response to extracellular pathogens and cancerous cells. But it can also reduce efficacy of large-molecule drugs by triggering anti-drug response. Significant progress has been made pMHCII modeling due collection large-scale pMHC mass spectrometry datasets (ligandomes) advances deep machine learning. Here, we develop graph-pMHC, a graph neural network approach predict...
The utility of deep neural nets has been demonstrated for mapping hematoxylin-and-eosin (H&E) stained image features to expression individual genes. However, these models have not employed discover clinically relevant spatial biomarkers. Here we develop MOSBY (Multi-Omic translation whole slide images Spatial Biomarker discoverY) that leverages contrastive self-supervised pretraining extract improved H&E features, learns a between and bulk omic profiles (RNA, DNA, protein), utilizes...
<title>Abstract</title> The epidemic of stripe rust, caused by the pathogen <italic>Puccinia Striiformis</italic> f. sp. <italic>tritici</italic> (<italic>Pst</italic>), would reduce wheat (<italic>Triticum aestivum</italic>) yields seriously. Traditional experimental methods are difficult to discover interaction between and <italic>Pst</italic>. Multi-omics data analysis provides a new idea for efficiently mining interactions host pathogen. We used 140 wheat-<italic>Pst</italic> RNA-Seq...
Bph14基因是第一个被克隆的水稻抗虫基因，但鲜有Bph14基因对水稻生理方面影响的报道。研究该基因对水稻生理方面的影响有助于全面理解Bph14基因对褐飞虱的抗性机制。将Bph14基因转入水稻栽培品种中，对携带有外源基因的转基因株系通过荧光定量PCR检测乙烯合成和非生物胁迫相关基因的表达，另外，分别用5 μmol/L ABA和250 mmol/L NaCl处理转基因水稻株系和相应受体材料，结果表明，与乙烯合成相关的基因OsACO2，OsACS2，OsACS6，O1gP5CS和O5gP5CS的表达量均较转基因受体m5274发生了变化，与干旱、耐盐等非生物胁迫相关的基因CatA、CatB、CatC、RAB16A、LEA3、LIP9、SalT、AdhI等也都不同于在受体m5274中的表达。同时Bph14基因的导入也提高了水稻对ABA的敏感性和对盐胁迫的耐受性，说明Bph14基因在水稻中可能参与调控乙烯合成以及非生物胁迫应答的功能基因的表达。