CufflinksCole Trapnell 
                        
                        
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            ESMFoldMeta 
                        
                        
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            About
            Cufflinks assemble transcripts, estimate their abundances and test for differential expression and regulation in RNA-Seq samples. It accepts aligned RNA-Seq reads and assembles the alignments into a parsimonious set of transcripts. Cufflinks then estimates the relative abundances of these transcripts based on how many reads support each one, taking into account biases in library preparation protocols. Cufflinks was originally developed as part of a collaborative effort between the Laboratory for Mathematical and Computational Biology. In order to make it easy to install Cufflinks, we provide a few binary packages to save users from the occasionally frustrating process of building Cufflinks, which requires that you install the libraries. Cufflinks includes a number of tools for analyzing RNA-Seq experiments. Some of these tools can be run on their own, while others are pieces of a larger workflow. 
             
            
        
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            About
            ESMFold shows how AI can give us new tools to understand the natural world, much like the microscope, which enabled us to see into the world at an infinitesimal scale and opened up a whole new understanding of life. AI can help us understand the immense scope of natural diversity, and see biology in a new way. Much of AI research has focused on helping computers understand the world in a way similar to how humans do. The language of proteins is one that is beyond human comprehension and has eluded even the most powerful computational tools. AI has the potential to open up this language to our understanding. Studying AI in new domains such as biology can also give insight into artificial intelligence more broadly. Our work reveals connections across domains: large language models that are behind advances in machine translation, natural language understanding, speech recognition, and image generation are also able to learn deep information about biology.
             
            
        
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        Audience
        Scientists requiring a solution to analyze their RNA-Seq samples
         
        
    
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        Researchers interested in a language model for proteins and genomics
         
        
    
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        Company InformationCole Trapnell 
    
    Founded: 2017 
    
    United States 
    cole-trapnell-lab.github.io/cufflinks/ 
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        Company InformationMeta 
    
    Founded: 2004 
    
    United States 
    github.com/facebookresearch/esm 
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