Search Results - "Rost, Burkhard"

Embeddings from deep learning transfer GO annotations beyond homology by Littmann, Maria, Heinzinger, Michael, Dallago, Christian, Olenyi, Tobias, Rost, Burkhard

“…Knowing protein function is crucial to advance molecular and medical biology, yet experimental function annotations through the Gene Ontology (GO) exist for…”
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TMbed: transmembrane proteins predicted through language model embeddings by Bernhofer, Michael, Rost, Burkhard

“…Despite the immense importance of transmembrane proteins (TMP) for molecular biology and medicine, experimental 3D structures for TMPs remain about 4-5 times…”
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Better prediction of functional effects for sequence variants by Hecht, Maximilian, Bromberg, Yana, Rost, Burkhard

“…Elucidating the effects of naturally occurring genetic variation is one of the major challenges for personalized health and personalized medicine. Here, we…”
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Modeling aspects of the language of life through transfer-learning protein sequences by Heinzinger, Michael, Elnaggar, Ahmed, Wang, Yu, Dallago, Christian, Nechaev, Dmitrii, Matthes, Florian, Rost, Burkhard

“…Predicting protein function and structure from sequence is one important challenge for computational biology. For 26 years, most state-of-the-art approaches…”
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Protein embeddings and deep learning predict binding residues for various ligand classes by Littmann, Maria, Heinzinger, Michael, Dallago, Christian, Weissenow, Konstantin, Rost, Burkhard

“…One important aspect of protein function is the binding of proteins to ligands, including small molecules, metal ions, and macromolecules such as DNA or RNA…”
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Evolutionary profiles improve protein-protein interaction prediction from sequence by Hamp, Tobias, Rost, Burkhard

“…Many methods predict the physical interaction between two proteins (protein-protein interactions; PPIs) from sequence alone. Their performance drops…”
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Rendering protein mutation movies with MutAmore by Weissenow, Konstantin, Rost, Burkhard

“…The success of AlphaFold2 in reliable protein three-dimensional (3D) structure prediction, assists the move of structural biology toward studies of protein…”
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Assessing the role of evolutionary information for enhancing protein language model embeddings by Erckert, Kyra, Rost, Burkhard

“…Embeddings from protein Language Models (pLMs) are replacing evolutionary information from multiple sequence alignments (MSAs) as the most successful input for…”
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ProtTrans: Toward Understanding the Language of Life Through Self-Supervised Learning by Elnaggar, Ahmed, Heinzinger, Michael, Dallago, Christian, Rehawi, Ghalia, Wang, Yu, Jones, Llion, Gibbs, Tom, Feher, Tamas, Angerer, Christoph, Steinegger, Martin, Bhowmik, Debsindhu, Rost, Burkhard

“…Computational biology and bioinformatics provide vast data gold-mines from protein sequences, ideal for Language Models (LMs) taken from Natural Language…”
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Fine-tuning protein language models boosts predictions across diverse tasks by Schmirler, Robert, Heinzinger, Michael, Rost, Burkhard

“…Prediction methods inputting embeddings from protein language models have reached or even surpassed state-of-the-art performance on many protein prediction…”
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More challenges for machine-learning protein interactions by Hamp, Tobias, Rost, Burkhard

“…Machine learning may be the most popular computational tool in molecular biology. Providing sustained performance estimates is challenging. The standard…”
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ISIS: interaction sites identified from sequence by Ofran, Yanay, Rost, Burkhard

“…Motivation: Large-scale experiments reveal pairs of interacting proteins but leave the residues involved in the interactions unknown. These interface residues…”
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Variant effect predictions capture some aspects of deep mutational scanning experiments by Reeb, Jonas, Wirth, Theresa, Rost, Burkhard

“…Deep mutational scanning (DMS) studies exploit the mutational landscape of sequence variation by systematically and comprehensively assaying the effect of…”
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Protein-protein interaction hotspots carved into sequences by Ofran, Yanay, Rost, Burkhard

“…Protein-protein interactions, a key to almost any biological process, are mediated by molecular mechanisms that are not entirely clear. The study of these…”
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MSAViewer: interactive JavaScript visualization of multiple sequence alignments by Yachdav, Guy, Wilzbach, Sebastian, Rauscher, Benedikt, Sheridan, Robert, Sillitoe, Ian, Procter, James, Lewis, Suzanna E, Rost, Burkhard, Goldberg, Tatyana

“…The MSAViewer is a quick and easy visualization and analysis JavaScript component for Multiple Sequence Alignment data of any size. Core features include…”
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FunFam protein families improve residue level molecular function prediction by Scheibenreif, Linus, Littmann, Maria, Orengo, Christine, Rost, Burkhard

“…The CATH database provides a hierarchical classification of protein domain structures including a sub-classification of superfamilies into functional families…”
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SNAP predicts effect of mutations on protein function by Bromberg, Yana, Yachdav, Guy, Rost, Burkhard

“…Many non-synonymous single nucleotide polymor-phisms (nsSNPs) in humans are suspected to impact protein function. Here, we present a publicly available server…”
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Review: Protein Secondary Structure Prediction Continues to Rise by Rost, Burkhard

“…Methods predicting protein secondary structure improved substantially in the 1990s through the use of evolutionary information taken from the divergence of…”
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LocTree2 predicts localization for all domains of life by Goldberg, Tatyana, Hamp, Tobias, Rost, Burkhard

“…Subcellular localization is one aspect of protein function. Despite advances in high-throughput imaging, localization maps remain incomplete. Several methods…”
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Three-Dimensional Structures of Membrane Proteins from Genomic Sequencing by Hopf, Thomas A., Colwell, Lucy J., Sheridan, Robert, Rost, Burkhard, Sander, Chris, Marks, Debora S.

“…We show that amino acid covariation in proteins, extracted from the evolutionary sequence record, can be used to fold transmembrane proteins. We use this…”
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