Can Machine learning Uncover Gene regulation?
Recent research shows that noncoding DNA performs the essential function of controlling/regulating the other expressed genes
Machine learning can uncover Gene regulation!
What is useful DNA?
Only 1% of the DNA codes for proteins in our genome. Remaining 99% is made of 'noncoding' DNA and has been referred to as 'junk DNA' as it does not carry instructions to build proteins. Research from the past two decades has shown that this noncoding DNA performs the essential function of controlling/regulating the other 'expressed genes'. This gene regulation is a critical function required in the cell as too much or too little of gene expression can lead to severe diseases. Additionally, precision is required to quickly turn off the expression of the genes when the need is over or, conversely, quickly turn on the genes when a sudden gene arises. Gene mutations in these noncoding DNA regions can occasionally cause an increased risk of type 2 diabetes and cancer.
Now that scientists have established that noncoding DNA is very essential for proper functioning of the cells, researchers have been trying to zoom into this 99% of the genome to understand better and characterize specific functions of different regions with different techniques, experiments and approaches.
Intersection of Genomics with Mathematics and Computer Science
The field of Genomics research is quickly evolving to one of the best examples of, when 'Mathematics & Computer science' meets 'Biology'. As normal human DNA sequence is known now, computer scientists and mathematicians are building models to find those critical regions associated with diseases. These models can interpret and compare data from thousands of individuals with mutations(in these noncoding regions of DNA) with normal individuals (with no mutations). On the other hand, biologists are tackling the same problem with a different set of tools - meaning laboratory experiments and model organisms experiments on mice model, worm models as there is a large similarity of our genome to these organisms ( theory of evolution! )
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Slow but steady wins the race! Just don't give up......says your immune system.
The pandemic of COVID-19 will certainly be documented in the history of infectious diseases. Almost all facets of human life were affected, and about 15 million people have lost their lives to it as of today. In this large number of covid related deaths, there was a proportion of patients who were already fighting other diseases like cancer. As cancer patients have a weaker immune system (tired of fighting cancer), these patients were at high risk of COVID-19 infection. It is for this reason that these patients were prioritized for receiving vaccines.
Vaccines stimulate the body's immune cells (T cells and B cells) to fight the disease. In the case of the COVID-19 vaccine being given to weak cancer patients, scientists still wondered if patients with weak immune systems would produce enough T cell and B cell response to the vaccine. What if their weak bodies just do not have enough functioning T Cells and B cells to protect them?
How does our immune system respond?
A recent study proved that even with a weaker immune system, patients could produce some level of T cells and B cell-mediated immunity towards COVID-19. Just after 1 dose, they were able to make some level of antibodies and about 90% of the patients were able to produce protective antibodies after the second dose. Additional findings were that solid tumor patients could respond to the vaccines more effectively than patients with blood cancers.
These differences could be because the T cells and B cells are already diseased in blood cancer and cannot do their usual job of responding to vaccines. This also correlates with the fact that blood cancer patients are overall more susceptible to infections/infectious diseases.
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