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README.md

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-# MLOmics: Benchmark for Machine Learning on Cancer Multi-Omics Data
-Framing the investigation of diverse cancers as a machine learning problem has recently shown significant potential in multi-omics analysis and cancer research. Empowering these successful machine learning models are the high-quality training datasets with sufficient data volume and adequate preprocessing. However, while there exist several public data portals including The Cancer Genome Atlas (TCGA) multi-omics initiative or open-bases such as the LinkedOmics, these databases are not off-the-shelf for existing machine learning models. In this paper we propose MLOmics, an open cancer multi-omics benchmark aiming at serving better the development and evaluation of bioinformatics and machine learning models. MLOmics contains 8,314 patient samples covering all 32 cancer types with four omics types, stratified features, and extensive baselines. Complementary support for downstream analysis and bio-knowledge linking are also included to support interdisciplinary analysis.
+# MLOmics: Cancer Multi-Omics Database for Machine Learning
+
+## Abstract
+Framing the investigation of diverse cancers as a machine learning problem has recently shown significant potential in multi-omics analysis and cancer research. Empowering these successful machine learning models are the high-quality training datasets with sufficient data volume and adequate preprocessing. However, while there exist several public data portals including The Cancer Genome Atlas (TCGA) multi-omics initiative or open-bases such as the LinkedOmics, these databases are not off-the-shelf for existing machine learning models. 
+We propose MLOmics, an open cancer multi-omics database aiming at serving better the development and evaluation of bioinformatics and machine learning models. MLOmics contains 8,314 patient samples covering all 32 cancer types with four omics types, stratified features, and extensive baselines. Complementary support for downstream analysis and bio-knowledge linking are also included to support interdisciplinary analysis.
 
 ## Data Records
-MLOmics framework consists of three major components:
-(1) main datasets that includes all cancer multi-omics datasets for various tasks; (2) baselines and metrics that provides the source code for baseline models and performance metrics and (3) downstream analysis tools and reources linking that provides tools for further analysis and links to additional biological resources. 
+The MLOmic main datasets are now accessible under the Creative Commons 4.0 Attribution (CC-BY-4.0), which supports its use for educational and research purposes. 
+The main datasets presented include all cancer multi-omics datasets corresponding to the various tasks.
 
-## Main Datasets
+### Main Datasets
 The Main Datasets repository is stored as csv files and is organized into three layers.
 The first layer contains three files corresponding to three different tasks: Classification_datasets, Clustering_datasets, and Imputation_datasets.
 The second layer includes files for specific tasks, such as GS-BRCA, ACC, and Imp-BRCA.