A comprehensive review of machine learning techniques for multi-omics data integration: challenges and applications in precision oncology.

Multi-omics data play a crucial role in precision medicine, mainly to understand the diverse biological interaction between different omics. Machine learning approaches have been extensively employed in this context over the years. This review aims to comprehensively summarize and categorize these advancements, focusing on the integration of multi-omics data, which includes genomics, transcriptomics, proteomics and metabolomics, alongside clinical data. We discuss various machine learning techniques and computational methodologies used for integrating distinct omics datasets and provide valuable insights into their application. The review emphasizes both the challenges and opportunities present in multi-omics data integration, precision medicine and patient stratification, offering practical recommendations for method selection in various scenarios. Recent advances in deep learning and network-based approaches are also explored, highlighting their potential to harmonize diverse biological information layers. Additionally, we present a roadmap for the integration of multi-omics data in precision oncology, outlining the advantages, challenges and implementation difficulties. Hence this review offers a thorough overview of current literature, providing researchers with insights into machine learning techniques for patient stratification, particularly in precision oncology. Contact:  anirban@klyuniv.ac.in.

Steroidal saponins from Chlorophytum orchidastrum.

Six new spirostane-type saponins (1-6), named orchidastrosides A-F, and chloromaloside D were isolated from an ethanol extract of the roots of Chlorophytum orchidastrum. The saponins have neotigogenin or neogitogenin as the aglycon and oligosaccharidic chains possessing seven to nine sugar units. Their structures were elucidated mainly by 2D NMR spectroscopic analyses (COSY, TOCSY, NOESY, HSQC, and HMBC) and FABMS and HRESIMS. Compounds 1-6 were tested for cytotoxicity against two human colon cancer cell lines, HCT 116 and HT-29.

Cytotoxic spirostane-type saponins from the roots of Chlorophytum borivilianum.

Four new spirostane-type saponins named borivilianosides E-H (1-4) were isolated from an ethanol extract of the roots of Chlorophytum borivilianum together with two known steroid saponins (5 and 6). The structures of 1-4 were elucidated using mainly 2D NMR spectroscopic techniques and mass spectrometry. The cytotoxicity of borivilianosides F (2), G (3), and H (4) and three known compounds was evaluated using two human colon cancer cell lines (HT-29 and HCT 116).

Nonribosomal Peptides from Marine Microbes and Their Antimicrobial and Anticancer Potential.

Marine environments are largely unexplored and can be a source of new molecules for the treatment of many diseases such as malaria, cancer, tuberculosis, HIV etc. The Marine environment is one of the untapped bioresource of getting pharmacologically active nonribosomal peptides (NRPs). Bioprospecting of marine microbes have achieved many remarkable milestones in pharmaceutics. Till date, more than 50% of drugs which are in clinical use belong to the nonribosomal peptide or mixed polyketide-nonribosomal peptide families of natural products isolated from marine bacteria, cyanobacteria and fungi. In recent years large numbers of nonribosomal have been discovered from marine microbes using multi-disciplinary approaches. The present review covers the NRPs discovered from marine microbes and their pharmacological potential along with role of genomics, proteomics and bioinformatics in discovery and development of nonribosomal peptides drugs.