AI in Biotechnology
Artificial Intelligence (AI) in Biotechnology
1.Diagnosis
Diagnostic issues are
data-driven and resolving them requires new data-science based approaches.
So by using innovative AI and machine-learning one can improve diagnostic accuracy and cut costs – improving patient safety worldwide.
So by using innovative AI and machine-learning one can improve diagnostic accuracy and cut costs – improving patient safety worldwide.
diagnostics.ai is playing
a part in this future by applying AI to diagnostics- making tests more
automated, accurate and thus safer.
Diagnosis is done with
the help of qPCR i.e Quantitative PCR(Polymerase Chain Reaction) which is used to detect, characterize and quantify Nucleic Acids.
2.Rare Diseases
2.Rare Diseases
Facial
recognition software is being combined with machine learning to help clinicians
diagnose rare diseases. Patient photos are analyzed using facial analysis and
deep learning to detect phenotypes that correlate with rare genetic disease.
3.Drug Discovery
Traditional drug
discovery methods are target-driven, i.e., a known target is
used to screen for small molecules that either interact with it or affect its
function in cells.
However, these methods are extremely limited
due to the complex nature of cellular interactions as well as limited knowledge
of intricate cellular pathways.
AI can
overcome these challenges by identifying novel interactions and inferring
functional importance of different components of a cellular pathway.
AI utilizes complex
algorithms and machine learning to extract meaningful information from a large
dataset, e.g., a dataset of RNA sequencing can be used to identify genes whose
expression correlates with a given cellular condition.
AI can also be used to
identify compounds that could bind to ‘undruggable targets’, i.e., proteins
whose structures are not defined. Through iterative simulations of interactions
of different compounds with small pieces of a protein, a predictive set of
compounds can be easily identified in a relatively small amount of time.
Phenomic AI (https://phenomic.ai/) and Cyclica (https://cyclicarx.com/) software are employing AI.
4.AI in Plant Sciences and Agriculture.
Phenomic AI (https://phenomic.ai/) and Cyclica (https://cyclicarx.com/) software are employing AI.
4.AI in Plant Sciences and Agriculture.
In a field in Switzerland, a solar powered robot that looks like a table on wheels scans the rows of crops with its camera, Identifies weeds and zaps them with Blue jet of liquid from its mechanical tentacles.
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