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The Impact of AlphaFold 3’s Open Source Release on Life Sciences, Medicine, and Pharmacology: Applications and Practical Guidance

AlphaFold 3 (AF3), developed by Google DeepMind, represents a major advancement in the field of biomolecular structure prediction. It is a state-of-the-art AI tool specifically designed to predict and analyze the three-dimensional structures of complex biomolecules and their interactions, encompassing proteins, DNA, RNA, and other biomolecules. AF3 transcends the limitations of previous versions by employing […]

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Imperfect AI Large Models Still Powerfully Propel Professional Fields

In recent years, artificial intelligence (AI) technology has advanced rapidly, especially with the increasingly widespread application of large models such as GPT-4, Claude, Gemini, WuDao 2.0, ERNIE, and PanGu-α. From natural language processing to image recognition and autonomous driving, AI large models have demonstrated immense potential across various fields. However, despite their outstanding capabilities in […]

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Application of Artificial Intelligence Models in Simulating and Prediction of Severe Cases After COVID-19 Infection

I. Generation of Simulation Data: To clearly present the analysis results, post-infection clinical symptoms of the virus are simulated using the common case-control pattern, simulating both severe and mild patients. Considering that some clinical phenotypic data (such as age) are highly correlated with post-infection symptoms, we set up 2 strongly correlated features. Additionally, we established […]

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Challenges of Bioinformatics, Computational Biology, and Big Data Analysis

Let’s start by comparing two common concepts, bioinformatics and computational biology. Bioinformatics actually originated in 1978 as a new concept proposed by Paulien Hogeweg: Theoretical Biology, which refers to a biological existence that is theoretical (generated by computation) and corresponds to experimental results. Today, bioinformatics has a clear positioning: it’s a tool-based discipline, specifically, the […]

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High-throughput biological experiments design

The design of high-throughput biological experiments requires careful consideration of various key factors to ensure the experiment’s effectiveness and reproducibility. High-throughput experiments, such as genomic sequencing, proteomics analyses, or cytomics studies, typically involve large numbers of samples and complex data analysis. Below are some important considerations: Clear Experimental Objectives Sample Selection and Processing Experimental Design […]