Martin Haubrock

743 total citations
20 papers, 470 citations indexed

About

Martin Haubrock is a scholar working on Molecular Biology, Oncology and Cancer Research. According to data from OpenAlex, Martin Haubrock has authored 20 papers receiving a total of 470 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 3 papers in Oncology and 2 papers in Cancer Research. Recurrent topics in Martin Haubrock's work include Bioinformatics and Genomic Networks (7 papers), Genomics and Chromatin Dynamics (7 papers) and RNA Research and Splicing (5 papers). Martin Haubrock is often cited by papers focused on Bioinformatics and Genomic Networks (7 papers), Genomics and Chromatin Dynamics (7 papers) and RNA Research and Splicing (5 papers). Martin Haubrock collaborates with scholars based in Germany, India and Czechia. Martin Haubrock's co-authors include Edgar Wingender, Jürgen Dönitz, Mathias Krull, Jie Li, Xu Hua, Anirban Mukhopadhyay, Folker Meyer, Jörn Kalinowski, Alexander Goesmann and Robert Giegerich and has published in prestigious journals such as Nucleic Acids Research, Bioinformatics and PLoS ONE.

In The Last Decade

Martin Haubrock

19 papers receiving 463 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Martin Haubrock Germany	12	371	118	50	42	30	20	470
William Yang United States	13	301 0.8×	98 0.8×	58 1.2×	55 1.3×	22 0.7×	26	436
Catherine Snow United Kingdom	3	411 1.1×	73 0.6×	53 1.1×	46 1.1×	48 1.6×	3	544
Anney Che United States	7	296 0.8×	70 0.6×	72 1.4×	28 0.7×	26 0.9×	9	433
Byoung-Ha Yoon South Korea	10	335 0.9×	111 0.9×	58 1.2×	89 2.1×	68 2.3×	18	503
Rosario M. Piro Italy	14	403 1.1×	76 0.6×	76 1.5×	24 0.6×	38 1.3×	29	600
Jin Hwan South Korea	10	308 0.8×	88 0.7×	27 0.5×	33 0.8×	23 0.8×	26	436
Andrew Tikhonov United Kingdom	4	519 1.4×	94 0.8×	62 1.2×	36 0.9×	47 1.6×	5	686
Niran Abeygunawardena United Kingdom	5	552 1.5×	87 0.7×	65 1.3×	24 0.6×	28 0.9×	5	657
Nimrod Rappoport Israel	7	497 1.3×	128 1.1×	58 1.2×	22 0.5×	21 0.7×	8	630

Countries citing papers authored by Martin Haubrock

Since Specialization

Citations

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

Fields of papers citing papers by Martin Haubrock

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Martin Haubrock

This figure shows the co-authorship network connecting the top 25 collaborators of Martin Haubrock. A scholar is included among the top collaborators of Martin Haubrock 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 Martin Haubrock. Martin Haubrock is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Beißbarth, Tim, et al.. (2024). The importance of DNA sequence for nucleosome positioning in transcriptional regulation. Life Science Alliance. 7(8). e202302380–e202302380. 1 indexed citations

Oliveira, Tiago De, Torben Rogge, Karsten Rauch, et al.. (2021). Effects of the Novel PFKFB3 Inhibitor KAN0438757 on Colorectal Cancer Cells and Its Systemic Toxicity Evaluation In Vivo. Cancers. 13(5). 1011–1011. 29 indexed citations

Ammer‐Herrmenau, Christoph, Ahmad Amanzada, Shiv K. Singh, et al.. (2021). Comprehensive Wet-Bench and Bioinformatics Workflow for Complex Microbiota Using Oxford Nanopore Technologies. mSystems. 6(4). e0075021–e0075021. 20 indexed citations

Spitzner, Melanie, Thomas Meyer, Niklas Engels, et al.. (2021). NOTCH Activation via gp130/STAT3 Signaling Confers Resistance to Chemoradiotherapy. Cancers. 13(3). 455–455. 11 indexed citations

Beißbarth, Tim, et al.. (2020). Constructing temporal regulatory cascades in the context of development and cell differentiation. PLoS ONE. 15(4). e0231326–e0231326.

Wingender, Edgar, et al.. (2017). TFClass: expanding the classification of human transcription factors to their mammalian orthologs. Nucleic Acids Research. 46(D1). D343–D347. 81 indexed citations

Haubrock, Martin, et al.. (2016). Computational Identification of Key Regulators in Two Different Colorectal Cancer Cell Lines. Frontiers in Genetics. 7. 42–42. 8 indexed citations

Haubrock, Martin, et al.. (2016). NF-Y Binding Site Architecture Defines a C-Fos Targeted Promoter Class. PLoS ONE. 11(8). e0160803–e0160803. 8 indexed citations

Schirmer, Markus, Alexander Schaudinn, Martin Haubrock, et al.. (2016). Relevance of Sp Binding Site Polymorphism inWWOXfor Treatment Outcome in Pancreatic Cancer. JNCI Journal of the National Cancer Institute. 108(5). djv387–djv387. 24 indexed citations

10.

Haubrock, Martin, et al.. (2015). Multiobjective triclustering of time-series transcriptome data reveals key genes of biological processes. BMC Bioinformatics. 16(1). 200–200. 23 indexed citations

11.

Brockmöller, Jürgen, et al.. (2015). Impact of Mineralocorticoid Receptor Polymorphisms on Urinary Electrolyte Excretion with and Without Diuretic Drugs. Pharmacogenomics. 16(2). 115–127. 2 indexed citations

12.

Wingender, Edgar, et al.. (2014). TFClass: a classification of human transcription factors and their rodent orthologs. Nucleic Acids Research. 43(D1). D97–D102. 82 indexed citations

13.

Haubrock, Martin, et al.. (2013). Coexpression and coregulation analysis of time-series gene expression data in estrogen-induced breast cancer cell. Algorithms for Molecular Biology. 8(1). 9–9. 30 indexed citations

14.

Gültaş, Mehmet, Martin Haubrock, Nesrin Tüysüz, & Stephan Waack. (2012). Coupled mutation finder: A new entropy-based method quantifying phylogenetic noise for the detection of compensatory mutations. BMC Bioinformatics. 13(1). 225–225. 8 indexed citations

15.

Haubrock, Martin, Jie Li, & Edgar Wingender. (2012). Using potential master regulator sites and paralogous expansion to construct tissue-specific transcriptional networks. BMC Systems Biology. 6(S2). S15–S15. 10 indexed citations

16.

Li, Jie, Xu Hua, Martin Haubrock, Jin Wang, & Edgar Wingender. (2012). The architecture of the gene regulatory networks of different tissues. Bioinformatics. 28(18). i509–i514. 22 indexed citations

17.

Wang, Jin, Martin Haubrock, Xu Hua, et al.. (2011). Regulatory coordination of clustered microRNAs based on microRNA-transcription factor regulatory network. BMC Systems Biology. 5(1). 199–199. 50 indexed citations

18.

Degenhardt, Juliana, et al.. (2007). DEEP--A tool for differential expression effector prediction. Nucleic Acids Research. 35(Web Server). W619–W624. 1 indexed citations

19.

Chen, Xin, et al.. (2005). Deriving an ontology for human gene expression sources from the CYTOMER database on human organs and cell types.. PubMed. 5(1). 61–6. 13 indexed citations

20.

Goesmann, Alexander, Martin Haubrock, Folker Meyer, Jörn Kalinowski, & Robert Giegerich. (2002). PathFinder: reconstruction and dynamic visualization of metabolic pathways. Bioinformatics. 18(1). 124–129. 47 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.

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