Michael Bernhofer - Concepedia

Author

Michael Bernhofer

Technical University of Munich ORCID

Also Known As

Bernhofer, Michael, Lea I M Krautheimer, M. Bernhofer, Michael Bernhofer

Publications

2.2K

Citations

H-Index

Concepts

All Affiliations

Technical University of Munich Institute for Advanced Study Weihenstephan-Triesdorf University of Applied Sciences Helmholtz Zentrum München Columbia University

About

Michael Bernhofer is an author at Technical University of Munich specializing in molecular biology, medicine, and engineering.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Engineering	4	4	262
2	Medicine	4	4	149
3	Natural Sciences	2	2	228
4	Health Sciences	1	1	81
5	Public Health	1	1	34

Michael Bernhofer

Publications

2.1K

Citations

H-Index

Page 1

	Year	Citations
PredictProtein—an open resource for online prediction of protein structural and functional features Guy Yachdav, Edda Kloppmann, László Kaján, Nucleic Acids Research	2014	614
LocTree3 prediction of localization Tatyana Goldberg, Maximilian Hecht, Tobias Hamp, Nucleic Acids Research	2014	346
PredictProtein - Predicting Protein Structure and Function for 29 Years Michael Bernhofer, Christian Dallago, Tim Karl, Nucleic Acids Research	2021	258
Embeddings from protein language models predict conservation and variant effects Céline Marquet, Michael Heinzinger, Tobias Olenyi, Human Genetics	2021	164
ProNA2020 predicts protein–DNA, protein–RNA, and protein–protein binding proteins and residues from sequence Jiajun Qiu, Michael Bernhofer, Michael Heinzinger, Journal of Molecular Biology Systems BiologyEngineeringNatural SciencesRna BiologyMolecular Biology	2020	137
TMbed: transmembrane proteins predicted through language model embeddings Michael Bernhofer, Burkhard Rost BMC Bioinformatics	2022	96
NLSdb—major update for database of nuclear localization signals and nuclear export signals Michael Bernhofer, Tatyana Goldberg, Silvana Wolf, Nucleic Acids Research EngineeringNuclear PhysicsNuclear DataGeneticsMolecular Biology	2017	91
CT-based radiomic features predict tumor grading and have prognostic value in patients with soft tissue sarcomas treated with neoadjuvant radiation therapy Jan C. Peeken, Michael Bernhofer, Matthew B. Spraker, Radiotherapy and Oncology Adaptive RadiotherapyMedical ImagingRadiation TherapyTumor GradingCt-based Radiomic Features	2019	81
TMSEG: Novel prediction of transmembrane helices Michael Bernhofer, Edda Kloppmann, Jonas Reeb, Proteins Structure Function and Bioinformatics	2016	68
Combining multimodal imaging and treatment features improves machine learning‐based prognostic assessment in patients with glioblastoma multiforme Jan C. Peeken, Tatyana Goldberg, Thomas Pyka, Cancer Medicine	2018	66

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