Helmy M
Globally invariant behavior of oncogenes and random genes at population but not at single cell level
Cancer is widely considered a genetic disease. Notably, recent works have highlighted that every human gene may possibly be associated with cancer. Thus, the distinction between genes that drive oncogenesis and those that are associated to the disease, but do not play a role, requires attention
ReadPerspective: Multiomics and Machine Learning Help Unleash the Alternative Food Potential of Microalgae
Keywords : microalgae, omics, machine learning, alternative proteins, systems biology
ReadMetabolomics and modelling approaches for systems metabolic engineering
Metabolic engineering involves the manipulation of microbes to produce desirable compounds through genetic engineering or synthetic biology approaches. Metabolomics involves the quantitation of intracellular and extracellular metabolites, where mass spectrometry and nuclear magnetic resonance based analytical instrumentation are often used. Here, the experimental designs, sample preparations, metabolite quenching and extraction are essential to the quantitative metabolomics workflow.
ReadApplication of GeneCloudOmics: Transcriptomic Data Analytics for Synthetic Biology
Part of the Methods in Molecular Biology book series (MIMB,volume 2553)
ReadThe transformation of our food system using cellular agriculture: What lies ahead and who will lead it?
Phthalate esters (PAE) are compounds derived by double esterification of phthalic acid (1,2-benzenedicarboxylic acid). Since the Industrial Revolution, low molecular weight phthalates such as dimethyl phthalate (DMP) and diethyl phthalate (DEP) have been used in pharmaceutical and manufacturing industries to confer flexibility to products used in personal care, infant care and medical devices1.
ReadGeneCloudOmics: A Data Analytic Cloud Platform for High-Throughput Gene Expression Analysis
Multi-dimensional biological data is rapidly accumulating, and it is expected that the size of the data will exceed astronomical levels by 2025 (Stephens et al., 2015). This resulted in the development of computational tools that became vital in driving scientific discovery in recent times (Markowetz, 2017). A parallel increase in the development of online servers and databases has also been witnessed (Helmy et al., 2016), raising a new set of challenges related to the usability and maintenance of all these tools (Mangul et al., 2019). About half of the computational biology tools were found to be difficult to install, 28% of them are unavailable online in the provided URLs, and many others are missing adequate documentation and manuals (Mangul et al., 2019). The problem gets more complex with the limited computational and coding skills of two-thirds of the biologists who use these tools (Schultheiss, 2011). On the other hand, it was also noted that bioinformatics tools that are easy to install and use are highly cited, indicating wider usability by the community and a larger contribution to scientific discovery (Mangul et al., 2019). Thus, more web-based tools that avoid installation difficulties and operating system compatibility issues, simple point-and-click tools are required to tackle multi-dimensional omics datasets.
ReadSystems Biology to Understand and Regulate Human Retroviral Proinflammatory Response
After the human genome sequencing project, it is now well-known that only a very minor component of the whole genome, that is, only about 1-2% constitute of protein-coding genes (1). The remaining sequences make up the numerous transcriptional and translational regulatory components, such as ribosomal DNA genes, transfer RNA genes, and non-coding DNA sequences. Notably, in mammalian cells, about half of the non-coding DNA sequences are transposable elements (TEs) (2).
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