Maximilian Hecht

3.0k total citations · 2 hit papers
6 papers, 1.0k citations indexed

About

Maximilian Hecht is a scholar working on Molecular Biology, Genetics and Pharmacology. According to data from OpenAlex, Maximilian Hecht has authored 6 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 4 papers in Genetics and 1 paper in Pharmacology. Recurrent topics in Maximilian Hecht's work include Genomics and Rare Diseases (4 papers), Genomics and Phylogenetic Studies (4 papers) and Bioinformatics and Genomic Networks (2 papers). Maximilian Hecht is often cited by papers focused on Genomics and Rare Diseases (4 papers), Genomics and Phylogenetic Studies (4 papers) and Bioinformatics and Genomic Networks (2 papers). Maximilian Hecht collaborates with scholars based in Germany, United States and United Kingdom. Maximilian Hecht's co-authors include Burkhard Rost, Yana Bromberg, Peter Hönigschmid, Tobias Hamp, Edda Kloppmann, Gerrit Vriend, Marco Punta, Andrea Schafferhans, Avner Schlessinger and Reinhard Schneider and has published in prestigious journals such as Nucleic Acids Research, Journal of Molecular Biology and Scientific Reports.

In The Last Decade

Maximilian Hecht

6 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 →
Better prediction of functional effects for sequence variants

2015 417 citations Maximilian Hecht, Yana Bromberg et al. BMC Genomics profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Maximilian Hecht Germany	6	724	261	98	73	66	6	1.0k
Jim Stalker United Kingdom	9	798 1.1×	231 0.9×	58 0.6×	50 0.7×	70 1.1×	11	1.3k
An Xiao United States	17	1.0k 1.4×	213 0.8×	154 1.6×	101 1.4×	57 0.9×	38	1.3k
Ileana R. León Brazil	16	683 0.9×	208 0.8×	61 0.6×	59 0.8×	59 0.9×	24	1.1k
Omar Wagih United Kingdom	14	1.1k 1.6×	211 0.8×	137 1.4×	84 1.2×	96 1.5×	17	1.4k
Monique Zahn‐Zabal Switzerland	14	906 1.3×	244 0.9×	94 1.0×	51 0.7×	37 0.6×	22	1.1k
Dustin E. Bosch United States	17	886 1.2×	164 0.6×	75 0.8×	59 0.8×	103 1.6×	48	1.4k
Michael Bernhofer Germany	12	632 0.9×	116 0.4×	85 0.9×	51 0.7×	50 0.8×	14	1.0k
Nancy Villa United States	19	593 0.8×	236 0.9×	77 0.8×	61 0.8×	169 2.6×	33	944
Yafeng Zhu China	16	642 0.9×	127 0.5×	98 1.0×	59 0.8×	72 1.1×	28	1.0k

Countries citing papers authored by Maximilian Hecht

Since Specialization

Citations

This map shows the geographic impact of Maximilian Hecht'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 Maximilian Hecht with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maximilian Hecht more than expected).

Fields of papers citing papers by Maximilian Hecht

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Maximilian Hecht. 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 Maximilian Hecht. The network helps show where Maximilian Hecht may publish in the future.

Co-authorship network of co-authors of Maximilian Hecht

This figure shows the co-authorship network connecting the top 25 collaborators of Maximilian Hecht. A scholar is included among the top collaborators of Maximilian Hecht 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 Maximilian Hecht. Maximilian Hecht 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:

6 of 6 papers shown

1.

Mahlich, Yannick, Jonas Reeb, Maximilian Hecht, et al.. (2017). Common sequence variants affect molecular function more than rare variants?. Scientific Reports. 7(1). 1608–1608. 16 indexed citations

2.

Reeb, Jonas, Maximilian Hecht, Yannick Mahlich, Yana Bromberg, & Burkhard Rost. (2016). Predicted Molecular Effects of Sequence Variants Link to System Level of Disease. PLoS Computational Biology. 12(8). e1005047–e1005047. 12 indexed citations

3.

Hecht, Maximilian, Yana Bromberg, & Burkhard Rost. (2015). Better prediction of functional effects for sequence variants. BMC Genomics. 16(S8). S1–S1. 417 indexed citations breakdown →

4.

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 →

5.

Hamp, Tobias, Stefan Seemayer, Esmeralda Vicedo, et al.. (2013). Homology-based inference sets the bar high for protein function prediction. BMC Bioinformatics. 14(S3). S7–S7. 51 indexed citations

6.

Hecht, Maximilian, Yana Bromberg, & Burkhard Rost. (2013). News from the Protein Mutability Landscape. Journal of Molecular Biology. 425(21). 3937–3948. 66 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