Michael Bernhofer

2.3k total citations · 1 hit paper
14 papers, 1.0k citations indexed

About

Michael Bernhofer is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Michael Bernhofer has authored 14 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 4 papers in Radiology, Nuclear Medicine and Imaging and 2 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Michael Bernhofer's work include Machine Learning in Bioinformatics (8 papers), RNA and protein synthesis mechanisms (7 papers) and Radiomics and Machine Learning in Medical Imaging (4 papers). Michael Bernhofer is often cited by papers focused on Machine Learning in Bioinformatics (8 papers), RNA and protein synthesis mechanisms (7 papers) and Radiomics and Machine Learning in Medical Imaging (4 papers). Michael Bernhofer collaborates with scholars based in Germany, United States and Tanzania. Michael Bernhofer's co-authors include Burkhard Rost, Tatyana Goldberg, Edda Kloppmann, Andrea Schafferhans, Peter Hönigschmid, Yana Bromberg, Gerrit Vriend, Marco Punta, Tobias Hamp and Maximilian Hecht and has published in prestigious journals such as Nucleic Acids Research, Bioinformatics and PLoS ONE.

In The Last Decade

Michael Bernhofer

14 papers receiving 1.0k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

PredictProtein—an open resource for online prediction of protein structural and functional features

2014 455 citations Guy Yachdav, Edda Kloppmann et al. Nucleic Acids Research profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Michael Bernhofer Germany	12	632	178	116	85	85	14	1.0k
Justin Bo‐Kai Hsu Taiwan	18	887 1.4×	226 1.3×	61 0.5×	122 1.4×	45 0.5×	28	1.4k
Meng‐Ru Ho Taiwan	25	1.2k 1.9×	103 0.6×	141 1.2×	70 0.8×	66 0.8×	56	1.7k
Riu Yamashita Japan	20	1.0k 1.6×	140 0.8×	130 1.1×	54 0.6×	115 1.4×	49	1.4k
Tomonori Kaneko Canada	17	1.0k 1.6×	144 0.8×	81 0.7×	78 0.9×	47 0.6×	43	1.4k
Dustin E. Bosch United States	17	886 1.4×	54 0.3×	164 1.4×	54 0.6×	75 0.9×	48	1.4k
Shigeki Sugawara Japan	18	495 0.8×	261 1.5×	96 0.8×	101 1.2×	73 0.9×	64	1.2k
Zhixi Su China	18	918 1.5×	102 0.6×	188 1.6×	97 1.1×	184 2.2×	74	1.3k
Javier Delgado Spain	18	900 1.4×	72 0.4×	178 1.5×	28 0.3×	59 0.7×	33	1.3k
Martha L. Hale United States	22	531 0.8×	140 0.8×	94 0.8×	62 0.7×	47 0.6×	60	1.3k

Countries citing papers authored by Michael Bernhofer

Since Specialization

Citations

This map shows the geographic impact of Michael Bernhofer's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Michael Bernhofer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Bernhofer more than expected).

Fields of papers citing papers by Michael Bernhofer

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael Bernhofer. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Michael Bernhofer. The network helps show where Michael Bernhofer may publish in the future.

Co-authorship network of co-authors of Michael Bernhofer

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Bernhofer. A scholar is included among the top collaborators of Michael Bernhofer based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Michael Bernhofer. Michael Bernhofer is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

14 of 14 papers shown

Olenyi, Tobias, Michael Heinzinger, Michael Bernhofer, et al.. (2022). LambdaPP : Fast and accessible protein‐specific phenotype predictions. Protein Science. 32(1). e4524–e4524. 10 indexed citations

Bernhofer, Michael & Burkhard Rost. (2022). TMbed: transmembrane proteins predicted through language model embeddings. BMC Bioinformatics. 23(1). 326–326. 46 indexed citations

Heinzinger, Michael, Tobias Olenyi, Christian Dallago, et al.. (2021). Embeddings from protein language models predict conservation and variant effects. Human Genetics. 141(10). 1629–1647. 87 indexed citations

Qiu, Jiajun, Michael Bernhofer, Michael Heinzinger, et al.. (2020). ProNA2020 predicts protein–DNA, protein–RNA, and protein–protein binding proteins and residues from sequence. Journal of Molecular Biology. 432(7). 2428–2443. 76 indexed citations

Peeken, Jan C., Michael Bernhofer, Matthew B. Spraker, et al.. (2019). CT-based radiomic features predict tumor grading and have prognostic value in patients with soft tissue sarcomas treated with neoadjuvant radiation therapy. Radiotherapy and Oncology. 135. 187–196. 60 indexed citations

Bernhofer, Michael, et al.. (2018). Correcting mistakes in predicting distributions. Bioinformatics. 34(19). 3385–3386. 4 indexed citations

Peeken, Jan C., Tatyana Goldberg, Michael Bernhofer, et al.. (2018). Treatment-related features improve machine learning prediction of prognosis in soft tissue sarcoma patients. Strahlentherapie und Onkologie. 194(9). 824–834. 11 indexed citations

Peeken, Jan C., Michael Bernhofer, Benedikt Wiestler, et al.. (2018). Radiomics in radiooncology – Challenging the medical physicist. Physica Medica. 48. 27–36. 69 indexed citations

Peeken, Jan C., Tatyana Goldberg, Thomas Pyka, et al.. (2018). Combining multimodal imaging and treatment features improves machine learning‐based prognostic assessment in patients with glioblastoma multiforme. Cancer Medicine. 8(1). 128–136. 48 indexed citations

10.

Ardern, Zachary, Tatyana Goldberg, Andrea Schafferhans, et al.. (2017). Discovery of numerous novel small genes in the intergenic regions of the Escherichia coli O157:H7 Sakai genome. PLoS ONE. 12(9). e0184119–e0184119. 23 indexed citations

11.

Bernhofer, Michael, et al.. (2017). NLSdb—major update for database of nuclear localization signals and nuclear export signals. Nucleic Acids Research. 46(D1). D503–D508. 64 indexed citations

12.

Bernhofer, Michael, Edda Kloppmann, Jonas Reeb, & Burkhard Rost. (2016). TMSEG: Novel prediction of transmembrane helices. Proteins Structure Function and Bioinformatics. 84(11). 1706–1716. 36 indexed citations

13.

Yachdav, Guy, Edda Kloppmann, László Kaján, et al.. (2014). PredictProtein—an open resource for online prediction of protein structural and functional features. Nucleic Acids Research. 42(W1). W337–W343. 455 indexed citations breakdown →

14.

Reeb, Jonas, Edda Kloppmann, Michael Bernhofer, & Burkhard Rost. (2014). Evaluation of transmembrane helix predictions in 2014. Proteins Structure Function and Bioinformatics. 83(3). 473–484. 22 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact