CBD2: A functional biomarker database for colorectal cancerSchool of Laboratory Medicine and Bioengineering, Hangzhou Medical College, Hangzhou, China.
School of Medicine, Institute of Medical Sciences, Örebro University, Örebro, Sweden.
Department of Radiotherapy and Oncology, The Second Affiliated Hospital of Soochow University, Suzhou, China.
Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, China.
Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, China.
Department of Otolaryngology, Guangzhou Women and Children's Medical Centre, Guangzhou, China.
MOE Key Laboratory of Geriatric Diseases and Immunology, Suzhou Key Laboratory of Pathogen Bioscience and Anti-infective Medicine, Department of Bioinformatics, Center for Systems Biology, School of Biology and Basic Medical Sciences, Suzhou Medical College of Soochow University, Suzhou, China; School of Medicine, The Chinese University of Hong Kong, Shenzhen, Shenzhen, China.
Department of Mathematics, University of California, San Diego, CA, United States.
Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Guangdong Eye Institute, Southern Medical University, Guangzhou, China.
Medical Research Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China; Department of Oncology and Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden; Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, China; Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, China.
MOE Key Laboratory of Geriatric Diseases and Immunology, Suzhou Key Laboratory of Pathogen Bioscience and Anti-infective Medicine, Department of Bioinformatics, Center for Systems Biology, School of Biology and Basic Medical Sciences, Suzhou Medical College of Soochow University, Suzhou, China.
Department of Oncology and Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden.
Vise andre og tillknytning
2024 (engelsk)Inngår i: iMeta, ISSN 2770-5986, E-ISSN 2770-596X, Vol. 3, nr 1, artikkel-id e155Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]
The rapidly evolving landscape of biomarkers for colorectal cancer (CRC) necessitates an integrative, updated repository. In response, we constructed the Colorectal Cancer Biomarker Database (CBD), which collected and displayed the curated biomedicine information for 870 CRC biomarkers in the previous study. Building on CBD, we have now developed CBD2, which includes information on 1569 newly reported biomarkers derived from different biological sources (DNA, RNA, protein, and others) and clinical applications (diagnosis, treatment, and prognosis). CBD2 also incorporates information on nonbiomarkers that have been identified as unsuitable for use as biomarkers in CRC. A key new feature of CBD2 is its network analysis function, by which users can investigate the visible and topological network between biomarkers and identify their relevant pathways. CBD2 also allows users to query a series of chemicals, drug combinations, or multiple targets, to enable multidrug, multitarget, multipathway analyses, toward facilitating the design of polypharmacological treatments for CRC. CBD2 is freely available at http://www.eyeseeworld.com/cbd.
sted, utgiver, år, opplag, sider
John Wiley & Sons, 2024. Vol. 3, nr 1, artikkel-id e155
Emneord [en]
biomarker, colorectal cancer, database, network analysis
HSV kategori
Identifikatorer
URN: urn:nbn:se:oru:diva-110211DOI: 10.1002/imt2.155ISI: 001112778000001PubMedID: 38868513Scopus ID: 2-s2.0-85178410575OAI: oai:DiVA.org:oru-110211DiVA, id: diva2:1819219
Merknad
This work was supported by the National Natural Science Foundation of China (Grant numbers: 32200545 and 32271292), and the GDPH Supporting Fund for Talent Program (Grant numbers: KJ012020633 and KJ012019530) from Guangdong Provincial People's Hospital. This work was also supported by the Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application (Grant number: 2022B121 2010011).
2023-12-132023-12-132024-10-08bibliografisk kontrollert