Article
Biochemical Research Methods
Michele Gentili, Leonardo Martini, Marialuisa Sponziello, Luca Becchetti
Summary: This work presents a Biological Random Walks (BRW) approach for prioritizing disease genes within the human interactome. The proposed method integrates multiple biological sources and is compared against established baselines in an extensive study.
Article
Biochemistry & Molecular Biology
Ji Yang, Hongchun Li, Fan Wang, Fei Xiao, Wenying Yan, Guang Hu
Summary: This study proposed a computational framework that combines biomolecular network modeling and structural dynamics analysis to facilitate the discovery of new drugs with potential activity in multiple sclerosis. The research suggested that TNF-alpha-induced protein 3 (TNFAIP3) could be a potential therapeutic target for MS.
ACS CHEMICAL NEUROSCIENCE
(2021)
Review
Biochemistry & Molecular Biology
Claudio Fiocchi
Summary: The recent advancements in technologies like sequencing and mass spectroscopy, combined with artificial intelligence-powered analytic tools, have revolutionized big data research in complex diseases, including inflammatory bowel disease (IBD). This review provides a comprehensive assessment of the current knowledge on omes, omics, and multi-omics in IBD, highlighting their importance in understanding disease mechanisms and potential clinical applications such as biomarker identification and precision medicine. The review also critically analyzes the limitations of current IBD multi-omics studies and suggests ways to optimize the use of multi-omics data for better clinical and therapeutic outcomes. Finally, the review predicts the future incorporation of multi-omics analyses in the routine management of IBD.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Chemistry, Analytical
Peng Zhao, Yongxiang Feng, Junhan Wu, Junwen Zhu, Jinlei Yang, Xiaoxiao Ma, Zheng Ouyang, Xinrong Zhang, Wenpeng Zhang, Wenhui Wang
Summary: Mass spectrometry (MS) has become a powerful tool for analyzing metabolome, lipidome, and proteome. However, analyzing multi-omics in single cells is still challenging. In this study, a streamlined strategy for efficient and automatic single-cell multi-omics analysis by MS was developed. The strategy includes the use of a microwell chip for housing single cells, an automated system for extracting metabolites, phospholipids, and proteins, and obtaining MS2 spectra from a single cell sample. The strategy was successfully applied to analyze cancer tissue samples and improved cell classification accuracy compared to single-omics analysis.
ANALYTICAL CHEMISTRY
(2023)
Article
Biotechnology & Applied Microbiology
Xiaobin Xie, Xiaowei Chen
Summary: Deciphering the core metabolites of Fanconi anemia (FA) using a multi-omics composite network proved to be effective in predicting and prioritizing disease candidate metabolites. The study identified the top 5 metabolites and co-expressed genes associated with FA, providing additional indicators closely linked to the disease.
JOURNAL OF MICROBIOLOGY AND BIOTECHNOLOGY
(2022)
Article
Biochemistry & Molecular Biology
Fei Luo, Zongjun Yu, Qian Zhou, Ancheng Huang
Summary: This review discusses the application of multi-omics in the discovery of plant signaling metabolites, highlighting how it addresses the challenges of known metabolites with unknown functions, unknown metabolites with known functions, and unknown metabolites and functions. The current limitations and future development of multi-omics in discovering plant signaling metabolites are also discussed.
Article
Multidisciplinary Sciences
Fasil Tekola-Ayele, Xuehuo Zeng, Suvo Chatterjee, Marion Ouidir, Corina Lesseur, Ke Hao, Jia Chen, Markos Tesfaye, Carmen J. Marsit, Tsegaselassie Workalemahu, Ronald Wapner
Summary: Abnormal birthweight is associated with increased risk for cardiometabolic diseases in later life. This study integrated placental methylation and gene expression data with genetic loci associated with birthweight to identify functional genes involved in fetal growth regulation.
NATURE COMMUNICATIONS
(2022)
Review
Biochemistry & Molecular Biology
Francis E. Agamah, Jumamurat R. Bayjanov, Anna Niehues, Kelechi F. Njoku, Michelle Skelton, Gaston K. Mazandu, Thomas H. A. Ederveen, Nicola Mulder, Emile R. Chimusa, Peter A. C. 't Hoen
Summary: Advances in omics technologies have enabled the holistic study of biological systems. Network-based integrative approaches have revolutionized multi-omics analysis by capturing interactions between different layers of omics data. These approaches can identify biomarkers, disease subtypes, crosstalk, causality, and molecular drivers, providing insights into the understanding and treatment of diseases like COVID-19. However, challenges remain in terms of reproducibility, heterogeneity, and interpretability of results in multi-omics network-based analysis.
FRONTIERS IN MOLECULAR BIOSCIENCES
(2022)
Review
Chemistry, Medicinal
Jessie James Limlingan Malit, Hiu Yu Cherie Leung, Pei-Yuan Qian
Summary: Large-scale genome-mining analyses have identified numerous cryptic biosynthetic gene clusters (BGCs) as a valuable source of novel bioactive natural products. Effective strategies and computational methods are essential for selecting appropriate BGCs for further characterization and production of natural products. Studies have successfully produced compounds with high chemical novelty, novel biosynthesis pathways, and potent bioactivities by prioritizing candidate BGCs based on different logics such as detection of resistance genes, phylogenomics analysis, and targeting specific chemical structures.
Article
Genetics & Heredity
Jianing Kang, Lisa David, Yangyang Li, Jing Cang, Sixue Chen
Summary: The elucidation of complex molecular networks requires integrative analysis of molecular features and changes at different levels of information flow and regulation, utilizing high throughput functional genomics tools such as transcriptomics, proteomics, metabolomics, and lipidomics. Different types of biomolecules require specific sample extraction procedures and analytical instrumentation, often necessitating multiple sets/aliquots of samples for extraction. The adaptation of a biphasic fractionation method to extract proteins, metabolites, and lipids from the same sample for LC-MS/MS multi-omics allows for analysis of a wide range of biological and molecular processes with advantages such as sample conservation, reproducibility, and correlation between different types of biomolecules.
FRONTIERS IN GENETICS
(2021)
Article
Biochemistry & Molecular Biology
Nivedhitha Mahendran, P. M. Durai Raj Vincent
Summary: Alzheimer's disease is a form of Dementia with uncertain mechanism and no vital genetic factor. Recent advancements in bioinformatics have enabled the discovery of genetic risk factors associated with Alzheimer's disease. A Deep Belief Network-based prediction model using DNA Methylation and Gene Expression Microarray Data has been developed, overcoming the challenge of high dimension low sample size. The proposed feature selection technique and prediction model outperform existing methods, indicating promising results for multi-omics data.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2023)
Review
Biochemical Research Methods
Zhaoqian Liu, Anjun Ma, Ewy Mathe, Marlena Merling, Qin Ma, Bingqiang Liu
Summary: The relationships between microbes and their hosts or environments are associated with critical diseases and ecological changes. High-throughput Omics technologies offer an opportunity for understanding the structures and functions of microbiome, but data analysis remains challenging. Network analyses provide an efficient way to understand complex microbial communities.
BRIEFINGS IN BIOINFORMATICS
(2021)
Article
Biochemical Research Methods
Chunman Zuo, Hao Dai, Luonan Chen
Summary: DCCA is a computational tool for joint analysis of single-cell multi-omics data, capable of dissecting cellular heterogeneity, denoising and aggregating data, and constructing links between multi-omics data. By fine-tuning networks and inferring new transcriptional regulatory relations, DCCA demonstrates superior capability in analyzing and understanding complex biological processes.
Article
Psychiatry
Dan He, Cong Fan, Mengling Qi, Yuedong Yang, David N. Cooper, Huiying Zhao
Summary: A new risk gene predictor, rGAT-omics, has been proposed, integrating multi-omics data to predict a series of high-risk genes related to schizophrenia, providing new insights into the molecular mechanisms underlying schizophrenia.
TRANSLATIONAL PSYCHIATRY
(2021)
Article
Plant Sciences
Yang Liu, Congyang Yi, Qian Liu, Chunhui Wang, Wenpeng Wang, Fangpu Han, Xiaojun Hu
Summary: This study investigated the mechanisms regulating seed size in peanut by using a multi-omics approach. Two mutants with bigger seed size were isolated and analyzed through whole genome sequencing and RNA-Seq analysis, leading to the identification of candidate genes associated with seed size.
Article
Geosciences, Multidisciplinary
Yan Tang, An Yin, Xi Xu, Kaixuan An, Yunpeng Zhang
Summary: Through provenance analysis of samples from the Songpan-Ganzi basin, this study concludes that the basin had a stable and locally sourced sediment system, with different sub-basins receiving sediments from different areas, which is consistent with the remnant ocean model.
Article
Engineering, Multidisciplinary
Yihang Tu, Ji Li, Jiawei Long, Lin Qin, Yunpeng Zhang, Yang Qiu, Meng Ge, Hu Zheng, En Li
Summary: This paper presents the application of microwave thermography in defect detection of absorbing coatings. The measurement principle of microwave thermography is studied by theoretical analysis and simulation, and an improved morphological edge detection algorithm based on dual-threshold segmentation is proposed to get defect features.
MEASUREMENT SCIENCE AND TECHNOLOGY
(2023)
Article
Biochemistry & Molecular Biology
Congxue Hu, Tengyue Li, Yingqi Xu, Xinxin Zhang, Feng Li, Jing Bai, Jing Chen, Wenqi Jiang, Kaiyue Yang, Qi Ou, Xia Li, Peng Wang, Yunpeng Zhang
Summary: CellMarker 2.0 is an updated database that provides experimentally supported markers of various cell types in different tissues of human and mouse. It also offers web tools for analyzing single cell sequencing data.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Biochemistry & Molecular Biology
Hongying Zhao, Xiangzhe Yin, Haotian Xu, Kailai Liu, Wangyang Liu, Lixia Wang, Caiyu Zhang, Lin Bo, Xicheng Lan, Shihua Lin, Ke Feng, Shangwei Ning, Yunpeng Zhang, Li Wang
Summary: The updated LncTarD 2.0 database is a comprehensive resource for studying the regulatory mechanisms of lncRNA in human diseases, and provides various tools for analysis and visualization.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Biochemistry & Molecular Biology
Qiuyan Guo, Peng Wang, Qian Liu, Yangyang Hao, Yue Gao, Yue Qi, Rongji Xu, Hongyan Chen, Mengyu Xin, Xiaoting Wu, Rui Sun, Hui Zhi, Yunpeng Zhang, Shangwei Ning, Xia Li
Summary: Understanding the multilevel interplay contributing to cell development trajectories is crucial for precision medicine and therapeutic exploration in tumor development. The CellTracer database provides gene expression profiles and development trajectories of different cell populations, allowing users to explore significant alterations and crosstalk among genes, biological contexts, cell characteristics, and clinical treatments.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Biochemistry & Molecular Biology
Tiantongfei Jiang, Weiwei Zhou, Qi Sheng, Jiaxin Yu, Yunjin Xie, Na Ding, Yunpeng Zhang, Juan Xu, Yongsheng Li
Summary: Single-cell transcriptome analysis using ImmCluster tool provides valuable insights into cellular heterogeneity and immune cell clustering in cancer microenvironments. It integrates large datasets from healthy tissues and tumor samples, and provides various analytic modules and online tools for exploring immune cell annotations.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Genetics & Heredity
Ji Li, Jiashuo Wu, Junwei Han
Summary: Through extensive analysis of the multi-omics dataset of breast cancer from the METABRIC cohort, we found that different breast cancer subtypes exhibit different tumor microenvironment heterogeneity. Basal-like and HER2-enriched subtypes are associated with high immune scores, expression of most immune regulatory targets, and immune cell infiltration, suggesting that these subtypes could be defined as immune hot tumors and suitable for immune checkpoint blockade therapy. In contrast, Luminal A and Luminal B subtypes are associated with low immune scores and immune cell infiltration, suggesting that these subtypes could be defined as immune cold tumors. Additionally, the Normal-like subtype has relatively high levels of both immune and stromal features, which indicates that the Normal-like subtype may be suitable for more diverse treatment strategies.
Article
Biochemistry & Molecular Biology
Wei Wang, Haiyan Yuan, Junwei Han, Wei Liu
Summary: Risk gene identification has been a significant focus in the past two decades. This study proposes a protein complex-based, group Lasso-logistic model (PCLassoLog) to discover risk protein complexes, which extends the understanding of the molecular mechanism of cancer. Experimental results show that PCLassoLog outperforms other models and identifies risk protein complexes with individual risk proteins and synergistic partners.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2023)
Article
Food Science & Technology
Peng Xu, Wenbin Sun, Kang Xu, Yunpeng Zhang, Qian Tan, Yiren Qing, Ranbing Yang
Summary: This study establishes a fast, non-destructive, and effective approach for defect detection in maize seeds based on hyperspectral imaging (HSI) technology combined with deep learning. The proposed CNN-FES model can effectively capture important feature information in the spectral data using a subset of 24 feature wavelengths. The designed CNN-ATM model achieves comparable classification performance with three commonly used machine learning methods and achieves high classification accuracy on both the training and test sets.
Article
Biochemical Research Methods
Yuqi Sheng, Jiashuo Wu, Xiangmei Li, Jiayue Qiu, Ji Li, Qinyu Ge, Liang Cheng, Junwei Han
Summary: Researchers developed a novel computational method called iATMEcell to identify abnormal tumor microenvironment (TME) cells associated with biological outcomes. They manually collected TME cell types and their corresponding gene signatures, constructed a weighted cell-cell crosstalk network, and used network propagation algorithm to identify significantly dysregulated TME cells.
BRIEFINGS IN BIOINFORMATICS
(2023)
Article
Biology
Yinchun Su, Jiashuo Wu, Xiangmei Li, Ji Li, Xilong Zhao, Bingyue Pan, Junling Huang, Qingfei Kong, Junwei Han
Summary: In order to identify potential drugs against COVID-19, researchers have developed a computational approach called DTSEA. This method effectively ranks genes and performs enrichment analysis on drug target sets to predict candidate drugs. The DTSEA method has shown high accuracy and reliability in predicting potential drugs for COVID-19.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Biochemistry & Molecular Biology
Qian Wang, Xiangmei Li, Jiayue Qiu, Yalan He, Jiashuo Wu, Ji Li, Wei Liu, Junwei Han
Summary: Immune checkpoint inhibitor therapy is effective for melanoma, but gene-based predictive biomarkers are unstable. This study proposes a novel pathway mutation signature (PMS) model that predicts the survival and efficacy of ICI therapy based on accumulated gene mutations in biological pathways.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Chong Gao, Liyan Dai, Yong Gao, Yunpeng Zhang, Chengyong Yu, En Li, Hu Zheng, Zhuoyue Zhang
Summary: This letter proposes an improved cylindrical cavity for high-sensitivity detection. The cavity is characterized by symmetric double ridges inside, which compress the electric field and significantly improve the detection sensitivity. By optimizing the ridge parameters, considering the compromise between detection sensitivity, quality factor, and fabrication technique, the cavity design is determined. The proposed cavity shows higher sensitivity per unit volume (0.32%) compared to related research works.
IEEE MICROWAVE AND WIRELESS TECHNOLOGY LETTERS
(2023)
Article
Biochemistry & Molecular Biology
Wei Wang, Haiyan Yuan, Junwei Han, Wei Liu
Summary: Risk gene identification has been a focus of attention in the past two decades. This study proposes a protein complex-based, group Lasso-logistic model (PCLassoLog) to discover risk protein complexes, which yields superior predictive performance and identifies close partners that synergize with individual risk proteins. Additionally, selection probabilities are calculated and other protein complex-based models are proposed to complement PCLassoLog in identifying reliable risk protein complexes.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2023)
Article
Medicine, Research & Experimental
Xiangmei Li, Yalan He, Ying Jiang, Bingyue Pan, Jiashuo Wu, Xilong Zhao, Junling Huang, Qian Wang, Liang Cheng, Junwei Han
Summary: Immunotherapy is a promising cancer therapy, but effective biomarkers are needed to identify responsive patients. This study developed a pathway analysis method, PathwayTMB, to identify genomic mutation pathways as potential biomarkers for immunotherapy. The method showed promising results in predicting clinical outcome and had superior predictive effect compared to TMB.
MOLECULAR THERAPY-NUCLEIC ACIDS
(2023)