🧵🧵 THREAD: #Bioinformatics and #AlphaFold 🧵🧵
1. #AlphaFold is a deep learning system developed by #DeepMind, to predict the 3D #structure of #proteins from their #aminoacid sequence.
2. #AlphaFold has been applied and tested extensively in the biennial #CASP (Critical Assessment of protein Structure Prediction) experiment, and has achieved state-of-the-art performance.
3. #AlphaFold uses a combination of #convolutional and recurrent #neural #networks, trained on large amounts of #protein #sequence and structure data.
4. #AlphaFold allows #bioinformaticians to quickly and accurately predict the 3D structure of #proteins, without the need for expensive and time-consuming experimental methods.
5. #AlphaFold enables #bioinformaticians to better understand the function, dynamics, and evolution of #proteins, and to design new drugs and therapies.
6. #AlphaFold is an example of the power and potential of #deep #learning in #bioinformatics, and of the close collaboration between academia and industry.
7. Cloud genomics is a leader in the field of bioinformatics and deep learning, providing expert advice and solutions to help researchers and organizations succeed in their projects.
Follow us on Twitter @cloudgenomics for more information and updates on bioinformatics and AlphaFold. #bioinformatics #computationalbiology #alphafold

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More from @CloudGenomics

Dec 12
🧵🧵 THREAD: #Bioinformatics applications - a deep dive into #pipelines and #workflows 🧵🧵
1. #Bioinformatics is the application of #computational techniques to the #analysis of #biological #data, such as #sequences, #structures, and #interactions, and is an essential field of modern biology and medicine.
2. #Bioinformatics has many exciting applications in various fields, such as #genetics, #genomics, #proteomics, and #metabolomics, that can provide new insights into the workings of living systems, and can help to advance science and society.
Read 8 tweets
Dec 11
🧵🧵 THREAD: 9 tips for successful #bioinformatics #projects 🧵🧵
1. Start by defining the aim, scope, and objectives of your project, and by identifying the #biological and #computational questions you want to answer.
2. Identify the #data sources, types, and formats, that are relevant and available for your project, and evaluate their quality, quantity, and suitability.
Read 11 tweets
Dec 9
🧵🧵 THREAD: 10 reasons why #bioinformaticians should use #Nextflow 🧵🧵
1. #Nextflow is an open-source platform for #bioinformatics #pipelines and #workflows, designed to make them #scalable, #reproducible, and #portable.
2. #Nextflow allows #bioinformaticians to write their #pipelines and #workflows in a simple and expressive domain-specific language, called #Nextflow Script.
Read 11 tweets
Dec 8
🧵🧵 THREAD: The role of #cloud #computing in #bioinformatics 🧵🧵
1. #Cloud #computing allows #bioinformaticians to access and analyze large and complex #biological #data sets in a fast, scalable, and cost-effective manner.
2. The #cloud provides a flexible and dynamic #infrastructure that can be easily adjusted to the changing needs and demands of #bioinformatics projects.
Read 8 tweets
Dec 7
🧵#Bioinformatics applied to genomics, a THREAD🧵🧵:
#Genomics is the study of the entire #genetic makeup of an #organism, including its #DNA sequence, #gene structure, and regulation of #gene #expression.
#Bioinformatics is the application of computational techniques, such as #machine #learning and data mining, to the analysis of large datasets of biological information, such as #genomic, #proteomic, and #metabolomic data.
Read 9 tweets
Dec 5
Are you interested in getting started in #bioinformatics but not sure where to begin? Here are some tips to help you get started on your journey. A THREAD🧵🧵:
Start by learning a high-level #programming language, such as #Python or #R, and familiarizing yourself with data structures and #algorithms commonly used in #bioinformatics. The #BioPython and #Bioconductor libraries are great resources for this.
Next, learn about #genomic data formats and standards, such as #FASTA, #FASTQ, and #GFF. This will allow you to effectively manipulate and analyze large-scale #genomic #datasets. The #NCBI SRA and #EBI ENA databases are great places to find real-world data to work with.
Read 12 tweets

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