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Maria Littmann
Maria Littmann
在 tum.de 的电子邮件经过验证
标题
引用次数
引用次数
年份
PredictProtein-predicting protein structure and function for 29 years
M Bernhofer, C Dallago, T Karl, V Satagopam, M Heinzinger, M Littmann, ...
Nucleic acids research 49 (W1), W535-W540, 2021
1892021
Embeddings from deep learning transfer GO annotations beyond homology
M Littmann, M Heinzinger, C Dallago, T Olenyi, B Rost
Scientific reports 11 (1), 1160, 2021
1212021
Learned embeddings from deep learning to visualize and predict protein sets
C Dallago, K Schütze, M Heinzinger, T Olenyi, M Littmann, AX Lu, ...
Current Protocols 1 (5), e113, 2021
802021
Protein embeddings and deep learning predict binding residues for various ligand classes
M Littmann, M Heinzinger, C Dallago, K Weissenow, B Rost
Scientific Reports 11 (1), 23916, 2021
782021
Contrastive learning on protein embeddings enlightens midnight zone
M Heinzinger, M Littmann, I Sillitoe, N Bordin, C Orengo, B Rost
NAR genomics and bioinformatics 4 (2), lqac043, 2022
682022
Validity of machine learning in biology and medicine increased through collaborations across fields of expertise
M Littmann, K Selig, L Cohen-Lavi, Y Frank, P Hönigschmid, E Kataka, ...
Nature Machine Intelligence 2 (1), 18-24, 2020
642020
AlphaFold2 reveals commonalities and novelties in protein structure space for 21 model organisms
N Bordin, I Sillitoe, V Nallapareddy, C Rauer, SD Lam, VP Waman, N Sen, ...
Communications biology 6 (1), 160, 2023
632023
Novel machine learning approaches revolutionize protein knowledge
N Bordin, C Dallago, M Heinzinger, S Kim, M Littmann, C Rauer, ...
Trends in Biochemical Sciences 48 (4), 345-359, 2023
462023
CATHe: detection of remote homologues for CATH superfamilies using embeddings from protein language models
V Nallapareddy, N Bordin, I Sillitoe, M Heinzinger, M Littmann, VP Waman, ...
Bioinformatics 39 (1), btad029, 2023
262023
Common sequence variants affect molecular function more than rare variants?
Y Mahlich, J Reeb, M Hecht, M Schelling, TAP De Beer, Y Bromberg, ...
Scientific reports 7 (1), 1608, 2017
262017
Clustering FunFams using sequence embeddings improves EC purity
M Littmann, N Bordin, M Heinzinger, K Schütze, C Dallago, C Orengo, ...
Bioinformatics 37 (20), 3449-3455, 2021
252021
FunFam protein families improve residue level molecular function prediction
L Scheibenreif, M Littmann, C Orengo, B Rost
BMC bioinformatics 20, 1-9, 2019
232019
Evolutionary couplings and sequence variation effect predict protein binding sites
M Schelling, TA Hopf, B Rost
Proteins: Structure, Function, and Bioinformatics 86 (10), 1064-1074, 2018
192018
LambdaPP: Fast and accessible protein‐specific phenotype predictions
T Olenyi, C Marquet, M Heinzinger, B Kröger, T Nikolova, M Bernhofer, ...
Protein Science 32 (1), e4524, 2023
92023
Detailed prediction of protein sub-nuclear localization
M Littmann, T Goldberg, S Seitz, M Bodén, B Rost
BMC bioinformatics 20, 1-15, 2019
72019
Alphafold2 reveals commonalities and novelties in protein structure space for 21 model organisms. bioRxiv, 2022
N Bordin, I Sillitoe, V Nallapareddy, C Rauer, SD Lam, VP Waman, N Sen, ...
URL https://www. biorxiv. org/content/early/2022/06/03/2022.06 2, 0
2
Refining Embedding-Based Binding Predictions by Leveraging AlphaFold2 Structures
L Endres, T Olenyi, K Erckert, K Weißenow, B Rost, M Littmann
bioRxiv, 2022.08. 31.505997, 2022
12022
Recombinant zoster vaccine and reduced risk of dementia: matched-cohort study using large-scale electronic health records and machine learning methodology
P Schwab, R Widenmaier, H Tahrat, M Littmann, B Anspach, ...
Alzheimer's Association International Conference, 2024
2024
Toxin Data Quality: A Critical Examination of Bacterial Exotoxins and Animal Toxins
T Krüger, I Koludarov, M Littmann, B Rost, LF Jimenez-Soto
2024
Deep learning cluster analysis reveals subtypes in response to antisense oligonucleotide therapy in chronic hepatitis B
C Weis, M Littmann, A Triastcyn, W Jordan, D Theodore, M Paff, H Tipney, ...
Journal of Hepatology 78, S1151-S1152, 2023
2023
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