Latest Techno Trends

  In Part 1 of the article on AI in COVID Drug and Vaccine development, we discussed about how AI is used extensively in any drug and vaccine development. In this part, we will look deeper into how AI is specifically being used in COVID-19 drug and vaccine development. The recent applications of Artificial Intelligence for COVID-19 include the virtual screening of both repurposed drug candidates and new chemical entities. For repurposed drugs, the goal has been to rapidly predict and exploit interconnected biological pathways or the off-target biology of existing medicines that are proven safe and can thus be readily tested in new clinical trials. Scientists leveraged AI-derived knowledge graph, which integrates biomedical data from structured and unstructured sources. Similarly, other scientists published an application of their Deep Learning-based drug–target interaction model that predicted commercially available antiviral drugs that may target the COVID-19-related protease and hel

 

  Coronavirus (COVID-19) has wreaked havoc across the world with more than 263 million infected cases and close to 5.2 million deaths as of 1st December 2021. The virus, coming from the family of Coronaviridae with its predecessors Severe Acute Respiratory Disease (SARS) and Middle Eastern Respiratory Syndrome (MERS), emerging in 2002 and 2013, respectively, has impacted human population across geographies with USA, Brazil and India emerging as the leading hotspots with more than 20 million confirmed cases each (USA has actually topped 48 million). Refer Bloomberg for current update on Mapping theCoronavirus Outbreak Across the World . UPDATE:  The Omicron variant — first identified in South Africa — was designated as a variant of concern  by the World Health Organization (WHO) recently.  It has become the fifth and latest variant of concern to be categorized as such since the start of the COVID-19 pandemic. A variant of concern has the potential for increased transmissibility, severit

  In the first part of the article on Data Science vs Machine Learning , we learned about the basic difference between Data Science and Machine Learning. Let us delve deep into the topic and also learn about deep learning and neural networks. We see a lot of data science projects in the online advertising industry. If analyzing data tells you, for example, that the travel industry is not buying a lot of ads, but if you send more salespeople to sell ads to travel companies, you could convince them to use more advertising, then that would be an example of a data science project and the data science provides conclusion and helps the executives deciding to ask a sales team to spend more time reaching out to the travel industry.    There is a good possibility that, within one company, you may have different machine learning and data science projects running simultaneously, both of which can be incredibly valuable.    You have also heard of deep learning. So, what is deep learning? Let's