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Konstantin Schütze

Showing results (1-10 of 9) with videos related to

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Frontiers in Bioinformatics|December 5, 2022
Nearest neighbor search on embeddings rapidly identifies distant protein relationsKonstantin Schütze, Michael Heinzinger, Martin Steinegger, et al.
Nature Methods|May 31, 2022
ColabFold: making protein folding accessible to allMilot Mirdita, Konstantin Schütze, Yoshitaka Moriwaki, et al.
Bioinformatics (Oxford, England)|May 12, 2021
Clustering FunFams using sequence embeddings improves EC purityMaria Littmann, Nicola Bordin, Michael Heinzinger, et al.
Nature Communications|May 3, 2025
Labelizer: systematic selection of protein residues for covalent fluorophore labelingChristian Gebhardt, Pascal Bawidamann, Anna-Katharina Spring, et al.
Current Protocols|May 7, 2021
Learned Embeddings from Deep Learning to Visualize and Predict Protein SetsChristian Dallago, Konstantin Schütze, Michael Heinzinger, et al.
Protein Science : a Publication of the Protein Society|December 1, 2022
LambdaPP: Fast and accessible protein-specific phenotype predictionsTobias Olenyi, Céline Marquet, Michael Heinzinger, et al.
Molecular & Cellular Proteomics : MCP|January 2, 2025
Molecular Display of the Animal Meta-Venome for Discovery of Novel Therapeutic PeptidesMeng-Hsuan Hsiao, Yang Miao, Zixing Liu, et al.
Biorxiv : the Preprint Server for Biology|June 10, 2024
Molecular Display of the Animal Meta-Venome for Discovery of Novel Therapeutic PeptidesMeng-Hsuan Hsiao, Yang Miao, Zixing Liu, et al.
Nucleic Acids Research|May 17, 2021
PredictProtein - Predicting Protein Structure and Function for 29 YearsMichael Bernhofer, Christian Dallago, Tim Karl, et al.
Pageof 1

Showing results (1-10 of 9) with videos related to

Sort By:
Pageof 1
Frontiers in Bioinformatics|December 5, 2022
Nearest neighbor search on embeddings rapidly identifies distant protein relationsKonstantin Schütze, Michael Heinzinger, Martin Steinegger, et al.
Nature Methods|May 31, 2022
ColabFold: making protein folding accessible to allMilot Mirdita, Konstantin Schütze, Yoshitaka Moriwaki, et al.
Bioinformatics (Oxford, England)|May 12, 2021
Clustering FunFams using sequence embeddings improves EC purityMaria Littmann, Nicola Bordin, Michael Heinzinger, et al.
Nature Communications|May 3, 2025
Labelizer: systematic selection of protein residues for covalent fluorophore labelingChristian Gebhardt, Pascal Bawidamann, Anna-Katharina Spring, et al.
Current Protocols|May 7, 2021
Learned Embeddings from Deep Learning to Visualize and Predict Protein SetsChristian Dallago, Konstantin Schütze, Michael Heinzinger, et al.
Protein Science : a Publication of the Protein Society|December 1, 2022
LambdaPP: Fast and accessible protein-specific phenotype predictionsTobias Olenyi, Céline Marquet, Michael Heinzinger, et al.
Molecular & Cellular Proteomics : MCP|January 2, 2025
Molecular Display of the Animal Meta-Venome for Discovery of Novel Therapeutic PeptidesMeng-Hsuan Hsiao, Yang Miao, Zixing Liu, et al.
Biorxiv : the Preprint Server for Biology|June 10, 2024
Molecular Display of the Animal Meta-Venome for Discovery of Novel Therapeutic PeptidesMeng-Hsuan Hsiao, Yang Miao, Zixing Liu, et al.
Nucleic Acids Research|May 17, 2021
PredictProtein - Predicting Protein Structure and Function for 29 YearsMichael Bernhofer, Christian Dallago, Tim Karl, et al.
Pageof 1