Konrad Zych

2.2k total citations
8 papers, 315 citations indexed

About

Konrad Zych is a scholar working on Molecular Biology, Oncology and Genetics. According to data from OpenAlex, Konrad Zych has authored 8 papers receiving a total of 315 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 3 papers in Oncology and 3 papers in Genetics. Recurrent topics in Konrad Zych's work include Genetic and phenotypic traits in livestock (2 papers), Gut microbiota and health (2 papers) and Genetic Mapping and Diversity in Plants and Animals (2 papers). Konrad Zych is often cited by papers focused on Genetic and phenotypic traits in livestock (2 papers), Gut microbiota and health (2 papers) and Genetic Mapping and Diversity in Plants and Animals (2 papers). Konrad Zych collaborates with scholars based in Netherlands, Poland and United Kingdom. Konrad Zych's co-authors include Per E. M. Siegbahn, Mariusz Radoń, Tomasz Borowski, Jakob Wirbel, Shinichi Sunagawa, Morgan Essex, Peer Bork, Ece Kartal, Guillem Salazar and Georg Zeller and has published in prestigious journals such as Journal of the American Chemical Society, Nucleic Acids Research and PLoS ONE.

In The Last Decade

Konrad Zych

8 papers receiving 311 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Konrad Zych Netherlands	7	205	80	46	37	30	8	315
Yifeng Yuan China	10	275 1.3×	34 0.4×	28 0.6×	17 0.5×	22 0.7×	34	399
Xiaoqian Hu China	15	216 1.1×	45 0.6×	44 1.0×	115 3.1×	10 0.3×	26	612
Corinne Sebban‐Kreuzer France	13	207 1.0×	18 0.2×	39 0.8×	11 0.3×	31 1.0×	26	354
A.F. Pinto Portugal	11	308 1.5×	63 0.8×	17 0.4×	28 0.8×	289 9.6×	19	559
Angela‐Nadia Albetel United States	6	240 1.2×	75 0.9×	13 0.3×	46 1.2×	14 0.5×	6	351
Nalin Abeydeera United States	10	195 1.0×	12 0.1×	15 0.3×	56 1.5×	28 0.9×	18	334
Tanya M Budiarto United States	6	203 1.0×	18 0.2×	65 1.4×	11 0.3×	137 4.6×	6	378
Takefumi Onodera Japan	9	163 0.8×	21 0.3×	37 0.8×	29 0.8×	54 1.8×	18	298
Mark P. G. van der Linden Netherlands	7	226 1.1×	27 0.3×	67 1.5×	17 0.5×	17 0.6×	13	372
Vincent Normant France	12	190 0.9×	8 0.1×	85 1.8×	76 2.1×	24 0.8×	20	335

Countries citing papers authored by Konrad Zych

Since Specialization

Citations

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

Fields of papers citing papers by Konrad Zych

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Konrad Zych

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

8 of 8 papers shown

1.

Wojciechowski, Szymon, et al.. (2022). Machine learning on the road to unlocking microbiota’s potential for boosting immune checkpoint therapy. International Journal of Medical Microbiology. 312(7). 151560–151560. 4 indexed citations

2.

Wirbel, Jakob, Konrad Zych, Morgan Essex, et al.. (2021). Microbiome meta-analysis and cross-disease comparison enabled by the SIAMCAT machine learning toolbox. Genome biology. 22(1). 141 indexed citations

3.

Carratore, Francesco Del, Konrad Zych, Matthew Cummings, et al.. (2019). Computational identification of co-evolving multi-gene modules in microbial biosynthetic gene clusters. Communications Biology. 2(1). 83–83. 21 indexed citations

4.

Zych, Konrad, Gerrit Gort, Chris Maliepaard, Ritsert C. Jansen, & Roeland E. Voorrips. (2019). FitTetra 2.0 – improved genotype calling for tetraploids with multiple population and parental data support. BMC Bioinformatics. 20(1). 148–148. 27 indexed citations

5.

Zych, Konrad, Basten L. Snoek, Mark Elvin, et al.. (2017). reGenotyper: Detecting mislabeled samples in genetic data. PLoS ONE. 12(2). e0171324–e0171324. 11 indexed citations

6.

Zych, Konrad, Yang Li, Joeri K. van der Velde, et al.. (2015). Pheno2Geno - High-throughput generation of genetic markers and maps from molecular phenotypes for crosses between inbred strains. BMC Bioinformatics. 16(1). 51–51. 7 indexed citations

7.

Velde, K. Joeri van der, Konrad Zych, Danny Arends, et al.. (2013). WormQTL^HD—a web database for linking human disease to natural variation data inC. elegans. Nucleic Acids Research. 42(D1). D794–D801. 17 indexed citations

8.

Borowski, Tomasz, et al.. (2010). Mechanism of Selective Halogenation by SyrB2: A Computational Study. Journal of the American Chemical Society. 132(37). 12887–12898. 87 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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