Joanna M. Wasiluk, PhD’s Post

"Oh, great! This could be an amazing tool to advance research. Maybe come up with something to help cure a terrible disease!" Was my first thought... And I REALLY, TRULY want that to be what happens. But I can't help but be a little skeptical. If it's "free", YOU are the product. If it's "free", what you build/make/discover using that tool is ultimately controlled or owned by the company that owns the tool. I used to believe Google's old motto, "Don't Be Evil" at least a little bit. I WANTED to believe it. I generally try to see the good things first. I am kind of naive that way. Perhaps too naive? I hope I am being just too cynical. Showing my age... This AI explosion is amazing in so many ways. I just want to see it benefit the many. Not the few. Rant over. Apologies, but if you made it this far, thanks. #ai #google #ethics #英語　＃ビジネス英語　＃コミュニケーション

My recent Vector Laboratories, Inc. blog post with Shuhui Chen, Ph.D. summarizes the evolution of #AI in #glycobiology, addressing current challenges and exciting solutions with great potential. Which #glycoinformatics tools are you familiar with?

Artificial intelligence (AI) is redefining possibilities in countless applications across the life sciences, and glycobiology is no exception. Glycobiologists have leveraged AI tools as early as the 1990s, but evolving machine-learning capabilities have enabled researchers to reach new frontiers in glycosylation site prediction, profiling, and more. Check out this blog by Vector Laboratories Research & Development Scientist Shuhui Chen, Ph.D. and Hikmet Emre Kaya to read more about how AI tools have powered progress in glycoinformatics and allowed researchers to elucidate the role of glycans in health and disease like never before: https://bit.ly/3QwQRPq #ArtificialIntelligence #MachineLearning #Glycobiology

Artificial Intelligence is proving to be an invaluable tool in fields of science. Here's a look at how utilizing deep learning AI in biology could improve medicine. #AI #ML #futurism #IntelligenceFactory #digitaltransformation #DX https://lnkd.in/gsH7W4JQ

Artificial Intelligence is proving to be an invaluable tool in fields of science. Here's a look at how utilizing deep learning AI in biology could improve medicine. #AI #ML #futurism #IntelligenceFactory #digitaltransformation #DX https://lnkd.in/grDqJ_dK

"By leveraging advanced AI algorithms, AlphaFold can predict the three-dimensional structure of a protein with remarkable accuracy, in a matter of days or even hours." #machinelearning #ai #alphafold #proteins #algorithms #computationalbiology

InnovationRx: Deepmind Unveils Its New Protein-Folding AI Model AlphaFold 3 Deepmind revealed the launch of AlphaFold 3, the next evolution of its revolutionary AI software for structural biology. This cutting-edge technology has already enabled thousands of researchers to predict the intricate chemical interactions involved with proteins, and the new iteration promises even greater capabilities. A Major Leap Forward One of the most significant advancements in AlphaFold 3 is its ability to predict not only protein folding but also the interactions of other crucial biological molecules, including DNA, RNA, and small molecules. Deepmind proudly published the accuracy of its predictions in the prestigious journal Nature. “The response to AlphaFold 2 was more than I could have ever imagined in terms of the kind of creativity and what the research community has done with it,” said John Jumper, Deepmind’s research director, at a press briefing. “And I can’t wait to see what they do with AlphaFold 3.” Increased Accessibility In addition to its expanded capabilities, Deepmind has launched the AlphaFold Server, a web service that allows researchers to generate biochemical models without the need to install the system’s open-source code, as was required with previous iterations. This move significantly enhances the accessibility of this groundbreaking technology for the scientific community. Another notable advancement is AlphaFold’s integration with diffusion models, which have gained popularity for their use in AI systems that generate images from text prompts. These models have now replaced some of AlphaFold’s previous structural models, further enhancing its predictive power. The Protein-Folding Challenge To appreciate the magnitude of AlphaFold’s achievement, it’s essential to understand the “protein-folding problem” that it has addressed. Proteins, the building blocks of all organic life, comprise long chains of amino acids that fold like ‘origami’ into 3D structures that determine their functions. Understanding how these structures fold opens the door to deciphering the molecular mechanisms that underpin health and disease. However, proteins can also become misfolded, a process that not only disrupts their normal function but also contributes to the development of diseases such as Alzheimer’s and Parkinson’s. Misfolding can interfere with cellular health by accumulating dysfunctional proteins that can damage cells and tissues. for the full article follow the link... https://lnkd.in/gUEEQMKW #AlphaFold3 #AI #ArtificialIntelligence #DhakaAi #AiInDhaka #AiinBangladesh #Vision2041

I admire those (rare) cases when true scientific research breakthroughs are given back to public to serve the whole of humanity. This mindblowing example, although it did not receive the widespread recognition it deserves, proves just that - and it can really speed up end-to-end drug discovery. This is the true success and measure of (so called) AI applicability - AI can be used not only to produce foolish short movie clips, it can help save lives.

PepCNN, a deep learning model, excels at predicting protein-peptide binding residues #AI #artificialintelligence #AUC #Biotechnology #Deeplearningmodel #DeepInsighttechnology #halfsphereexposure #llm #machinelearning #MCC #PepCNN #peptidebindingresidues #pretrainedlanguagemodels #Precision #sensitivity #sequencebaseddata #specificity #structuraldata