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Lian X, Zhang Y, Zhou Y, Sun X, Huang S, Dai H, Han L, Zhu F. SingPro: a knowledge base providing single-cell proteomic data. Nucleic Acids Res 2024; 52:D552-D561. [PMID: 37819028 PMCID: PMC10767818 DOI: 10.1093/nar/gkad830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2023] [Revised: 09/03/2023] [Accepted: 09/25/2023] [Indexed: 10/13/2023] Open
Abstract
Single-cell proteomics (SCP) has emerged as a powerful tool for detecting cellular heterogeneity, offering unprecedented insights into biological mechanisms that are masked in bulk cell populations. With the rapid advancements in AI-based time trajectory analysis and cell subpopulation identification, there exists a pressing need for a database that not only provides SCP raw data but also explicitly describes experimental details and protein expression profiles. However, no such database has been available yet. In this study, a database, entitled 'SingPro', specializing in single-cell proteomics was thus developed. It was unique in (a) systematically providing the SCP raw data for both mass spectrometry-based and flow cytometry-based studies and (b) explicitly describing experimental detail for SCP study and expression profile of any studied protein. Anticipating a robust interest from the research community, this database is poised to become an invaluable repository for OMICs-based biomedical studies. Access to SingPro is unrestricted and does not mandate a login at: http://idrblab.org/singpro/.
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Affiliation(s)
- Xichen Lian
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China
- Greater Bay Area Institute of Precision Medicine (Guangzhou), School of Life Sciences, Fudan University, Shanghai 315211, China
- Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare, Hangzhou 330110, China
| | - Yintao Zhang
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China
| | - Ying Zhou
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China
- State Key Laboratory for Diagnosis and Treatment of Infectious Disease, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang Provincial Key Laboratory for Drug Clinical Research and Evaluation, The First Affiliated Hospital, Zhejiang University, Hangzhou 310000, China
| | - Xiuna Sun
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China
| | - Shijie Huang
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China
| | - Haibin Dai
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China
| | - Lianyi Han
- Greater Bay Area Institute of Precision Medicine (Guangzhou), School of Life Sciences, Fudan University, Shanghai 315211, China
| | - Feng Zhu
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China
- Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare, Hangzhou 330110, China
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Zhang Y, Zhou Y, Zhou Y, Yu X, Shen X, Hong Y, Zhang Y, Wang S, Mou M, Zhang J, Tao L, Gao J, Qiu Y, Chen Y, Zhu F. TheMarker: a comprehensive database of therapeutic biomarkers. Nucleic Acids Res 2024; 52:D1450-D1464. [PMID: 37850638 PMCID: PMC10767989 DOI: 10.1093/nar/gkad862] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 09/21/2023] [Accepted: 09/29/2023] [Indexed: 10/19/2023] Open
Abstract
Distinct from the traditional diagnostic/prognostic biomarker (adopted as the indicator of disease state/process), the therapeutic biomarker (ThMAR) has emerged to be very crucial in the clinical development and clinical practice of all therapies. There are five types of ThMAR that have been found to play indispensable roles in various stages of drug discovery, such as: Pharmacodynamic Biomarker essential for guaranteeing the pharmacological effects of a therapy, Safety Biomarker critical for assessing the extent or likelihood of therapy-induced toxicity, Monitoring Biomarker indispensable for guiding clinical management by serially measuring patients' status, Predictive Biomarker crucial for maximizing the clinical outcome of a therapy for specific individuals, and Surrogate Endpoint fundamental for accelerating the approval of a therapy. However, these data of ThMARs has not been comprehensively described by any of the existing databases. Herein, a database, named 'TheMarker', was therefore constructed to (a) systematically offer all five types of ThMAR used at different stages of drug development, (b) comprehensively describe ThMAR information for the largest number of drugs among available databases, (c) extensively cover the widest disease classes by not just focusing on anticancer therapies. These data in TheMarker are expected to have great implication and significant impact on drug discovery and clinical practice, and it is freely accessible without any login requirement at: https://idrblab.org/themarker.
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Affiliation(s)
- Yintao Zhang
- College of Pharmaceutical Sciences, The First Affiliated Hospital, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China
- Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare, Hangzhou 330110, China
| | - Ying Zhou
- College of Pharmaceutical Sciences, The First Affiliated Hospital, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China
- National Key Laboratory of Diagnosis and Treatment of Severe Infectious Disease, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang Provincial Key Laboratory for Drug Clinical Research and Evaluation, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310000, China
| | - Yuan Zhou
- College of Pharmaceutical Sciences, The First Affiliated Hospital, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China
| | - Xinyuan Yu
- College of Pharmaceutical Sciences, The First Affiliated Hospital, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China
| | - Xinyi Shen
- Department of Environmental Health Sciences, Yale School of Public Health, Yale University, New Haven 06510, USA
| | - Yanfeng Hong
- Key Laboratory of Elemene Class Anti-Cancer Chinese Medicines, School of Pharmacy, Hangzhou Normal University, Hangzhou 311121, China
| | - Yuxin Zhang
- College of Pharmaceutical Sciences, The First Affiliated Hospital, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China
| | - Shanshan Wang
- Qian Xuesen Collaborative Research Center of Astrochemistry and Space Life Sciences, Institute of Drug Discovery Technology, Ningbo University, Ningbo 315211, China
| | - Minjie Mou
- College of Pharmaceutical Sciences, The First Affiliated Hospital, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China
| | - Jinsong Zhang
- College of Pharmaceutical Sciences, The First Affiliated Hospital, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China
| | - Lin Tao
- Key Laboratory of Elemene Class Anti-Cancer Chinese Medicines, School of Pharmacy, Hangzhou Normal University, Hangzhou 311121, China
| | - Jianqing Gao
- College of Pharmaceutical Sciences, The First Affiliated Hospital, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China
| | - Yunqing Qiu
- College of Pharmaceutical Sciences, The First Affiliated Hospital, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China
- National Key Laboratory of Diagnosis and Treatment of Severe Infectious Disease, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang Provincial Key Laboratory for Drug Clinical Research and Evaluation, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310000, China
| | - Yuzong Chen
- State Key Laboratory of Chemical Oncogenomics, Key Laboratory of Chemical Biology, The Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, China
- Institute of Biomedical Health Technology and Engineering, Shenzhen Bay Laboratory, Shenzhen 518000, China
| | - Feng Zhu
- College of Pharmaceutical Sciences, The First Affiliated Hospital, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China
- Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare, Hangzhou 330110, China
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Wang Y, Pan Z, Mou M, Xia W, Zhang H, Zhang H, Liu J, Zheng L, Luo Y, Zheng H, Yu X, Lian X, Zeng Z, Li Z, Zhang B, Zheng M, Li H, Hou T, Zhu F. A task-specific encoding algorithm for RNAs and RNA-associated interactions based on convolutional autoencoder. Nucleic Acids Res 2023; 51:e110. [PMID: 37889083 PMCID: PMC10682500 DOI: 10.1093/nar/gkad929] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 08/01/2023] [Accepted: 10/10/2023] [Indexed: 10/28/2023] Open
Abstract
RNAs play essential roles in diverse physiological and pathological processes by interacting with other molecules (RNA/protein/compound), and various computational methods are available for identifying these interactions. However, the encoding features provided by existing methods are limited and the existing tools does not offer an effective way to integrate the interacting partners. In this study, a task-specific encoding algorithm for RNAs and RNA-associated interactions was therefore developed. This new algorithm was unique in (a) realizing comprehensive RNA feature encoding by introducing a great many of novel features and (b) enabling task-specific integration of interacting partners using convolutional autoencoder-directed feature embedding. Compared with existing methods/tools, this novel algorithm demonstrated superior performances in diverse benchmark testing studies. This algorithm together with its source code could be readily accessed by all user at: https://idrblab.org/corain/ and https://github.com/idrblab/corain/.
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Affiliation(s)
- Yunxia Wang
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Polytechnic Institute, Zhejiang University, Hangzhou 310058, China
| | - Ziqi Pan
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Polytechnic Institute, Zhejiang University, Hangzhou 310058, China
| | - Minjie Mou
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Polytechnic Institute, Zhejiang University, Hangzhou 310058, China
| | - Weiqi Xia
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Polytechnic Institute, Zhejiang University, Hangzhou 310058, China
| | - Hongning Zhang
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Polytechnic Institute, Zhejiang University, Hangzhou 310058, China
| | - Hanyu Zhang
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Polytechnic Institute, Zhejiang University, Hangzhou 310058, China
| | - Jin Liu
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Polytechnic Institute, Zhejiang University, Hangzhou 310058, China
| | - Lingyan Zheng
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Polytechnic Institute, Zhejiang University, Hangzhou 310058, China
- Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Alibaba-ZJU Joint Research Center of Future Digital Healthcare, Hangzhou 330110, China
| | - Yongchao Luo
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Polytechnic Institute, Zhejiang University, Hangzhou 310058, China
| | - Hanqi Zheng
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Polytechnic Institute, Zhejiang University, Hangzhou 310058, China
| | - Xinyuan Yu
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Polytechnic Institute, Zhejiang University, Hangzhou 310058, China
| | - Xichen Lian
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Polytechnic Institute, Zhejiang University, Hangzhou 310058, China
| | - Zhenyu Zeng
- Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Alibaba-ZJU Joint Research Center of Future Digital Healthcare, Hangzhou 330110, China
| | - Zhaorong Li
- Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Alibaba-ZJU Joint Research Center of Future Digital Healthcare, Hangzhou 330110, China
| | - Bing Zhang
- Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Alibaba-ZJU Joint Research Center of Future Digital Healthcare, Hangzhou 330110, China
| | - Mingyue Zheng
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Polytechnic Institute, Zhejiang University, Hangzhou 310058, China
- Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
| | - Honglin Li
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Polytechnic Institute, Zhejiang University, Hangzhou 310058, China
- School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China
| | - Tingjun Hou
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Polytechnic Institute, Zhejiang University, Hangzhou 310058, China
| | - Feng Zhu
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Polytechnic Institute, Zhejiang University, Hangzhou 310058, China
- Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Alibaba-ZJU Joint Research Center of Future Digital Healthcare, Hangzhou 330110, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China
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Zhang H, Lu M, Lin G, Zheng L, Zhang W, Xu Z, Zhu F. SoCube: an innovative end-to-end doublet detection algorithm for analyzing scRNA-seq data. Brief Bioinform 2023; 24:7081128. [PMID: 36941114 DOI: 10.1093/bib/bbad104] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Revised: 02/17/2023] [Accepted: 02/28/2023] [Indexed: 03/23/2023] Open
Abstract
Doublets formed during single-cell RNA sequencing (scRNA-seq) severely affect downstream studies, such as differentially expressed gene analysis and cell trajectory inference, and limit the cellular throughput of scRNA-seq. Several doublet detection algorithms are currently available, but their generalization performance could be further improved due to the lack of effective feature-embedding strategies with suitable model architectures. Therefore, SoCube, a novel deep learning algorithm, was developed to precisely detect doublets in various types of scRNA-seq data. SoCube (i) proposed a novel 3D composite feature-embedding strategy that embedded latent gene information and (ii) constructed a multikernel, multichannel CNN-ensembled architecture in conjunction with the feature-embedding strategy. With its excellent performance on benchmark evaluation and several downstream tasks, it is expected to be a powerful algorithm to detect and remove doublets in scRNA-seq data. SoCube is freely provided as an end-to-end tool on the Python official package site PyPi (https://pypi.org/project/socube/) and open-source on GitHub (https://github.com/idrblab/socube/).
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Affiliation(s)
- Hongning Zhang
- Polytechnic Institute, The Second Affiliated Hospital, College of Pharmaceutical Sciences, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China
| | - Mingkun Lu
- Polytechnic Institute, The Second Affiliated Hospital, College of Pharmaceutical Sciences, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China
| | - Gaole Lin
- Polytechnic Institute, The Second Affiliated Hospital, College of Pharmaceutical Sciences, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China
| | - Lingyan Zheng
- Polytechnic Institute, The Second Affiliated Hospital, College of Pharmaceutical Sciences, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China
| | - Wei Zhang
- Polytechnic Institute, The Second Affiliated Hospital, College of Pharmaceutical Sciences, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China
| | - Zhijian Xu
- Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
| | - Feng Zhu
- Polytechnic Institute, The Second Affiliated Hospital, College of Pharmaceutical Sciences, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China
- Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare, Hangzhou 330110, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China
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