MyeloDB is a comprehensive database that provides access to a wealth of information related to multiple myeloma, a type of cancer that affects the plasma cells in bone marrow. The database is designed to help researchers, clinicians, and patients better understand multiple myeloma and develop new treatments for the disease.
MyeloDB includes a wide range of information related to multiple myeloma, including expression profile, methylation profile, CRISPR-Cas9 screens, mutation and biomarker data. One of the key features of MyeloDB is its search functionality, which allows users to search the database for specific information related to multiple myeloma. Users can search for keywords, phrases, or specific genes to find relevant information. The search results provide detailed information about each result, including links to articles, and other resources in addition to this files for each study can be downloaded.
In addition to its search functionality, MyeloDB also includes a variety of other features designed to help users navigate the database and find the information they need. These features include interactive visualization tools, data downloads, and a user-friendly interface. Overall, MyeloDB is a valuable resource for anyone interested in multiple myeloma, including researchers, clinicians, and patients. Its comprehensive database and user-friendly interface make it an invaluable tool for advancing our understanding of multiple myeloma and developing new treatments for the disease.

Terms of use:

Data Usage: The available data can be utilized exclusively for non-commercial purposes.
Citation: Kindly give credit to MyeloDB in your publications by citing us.
Disclaimer: MyeloDB serves as a database for multiple myeloma and aims to offer comprehensive information about the disease. However, it is important to note that the information provided in MyeloDB is not intended to replace professional medical advice or treatment from qualified healthcare professionals. Users of MyeloDB are advised to exercise their own discretion and judgment when interpreting and utilizing the information provided. MyeloDB holds no responsibility for any consequences that may arise from the use of the information available in the database.

Home The home page is the landing page of MyeloDB. It provides an overview and statistics of the database, and its various features. Datasets: The datasets section of MyeloDB allows users to explore and download various types of data related to multiple myeloma. This includes expression data, methylation data, and other types of data that can be used for research and analysis. Analysis: The analysis section of MyeloDB provides users with powerful tools for analyzing and visualizing data related to multiple myeloma. This includes interactive visualizations, statistical analysis tools, and other features that enable users to explore and interpret data in new ways. Biomarkers: The biomarkers section of MyeloDB provides information about the various biomarkers that have been identified in relation to multiple myeloma. This includes genetic biomarkers, protein biomarkers, and other types of biomarkers that can be used to diagnose and treat the disease. Downloads: The downloads section of MyeloDB provides users with access to data available in the database. This wllows user to download data that can be used for research and analysis. Help: The help section of MyeloDB is designed to provide users with assistance and guidance on using the various features and functions of the database. This includes tutorials, FAQs, and other resources that can help users get the most out of MyeloDB. Team: The team section of MyeloDB provides information about the researchers who are responsible for developing and maintaining the database.

USER MANUAL

1. Expression data profile: A collection of gene expression measurements for a set of genes across a set of samples. These measurements can be obtained using techniques such as microarray analysis or RNA sequencing.
2. Methylation data profile: A collection of methylation measurements for a set of genomic regions across a set of samples. Methylation data profiles can be obtained using techniques such as bisulfite sequencing or methylation microarrays.
3. Profiling technique: A method for measuring the expression of genes or proteins in biological samples, such as cells or tissues. Examples of profiling techniques include microarray analysis and RNA sequencing.
4. GEO (Gene Expression Omnibus): A public database that contains gene expression data from a wide range of organisms and experimental conditions.
5. GSE (Gene Expression Series): A series of related gene expression experiments that have been deposited in GEO. Each GSE is assigned a unique accession number for easy reference.
6. Data processing: The process of transforming raw data into a format that is suitable for analysis. This can involve tasks such as quality control, normalization, and filtering.
7. RMA normalization: A method for normalizing gene expression data that is commonly used with microarray data. RMA stands for Robust Multi-Array Average.
8. TPM (Transcripts Per Million): A normalization method used with RNA sequencing data that accounts for differences in library size and gene length.
9. RPKM (Reads Per Kilobase Million): A normalization method used with RNA sequencing data that accounts for differences in library size and gene length, similar to TPM.
10. CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats): A gene-editing technology that allows for precise modifications to be made to DNA sequences.
11. Achilles: A CRISPR-based genetic screening platform that is used to identify essential genes and genetic vulnerabilities in cancer cells.