Jan Mocák

2.0k total citations · 1 hit paper
72 papers, 1.6k citations indexed

About

Jan Mocák is a scholar working on Analytical Chemistry, Electrochemistry and Bioengineering. According to data from OpenAlex, Jan Mocák has authored 72 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Analytical Chemistry, 23 papers in Electrochemistry and 14 papers in Bioengineering. Recurrent topics in Jan Mocák's work include Electrochemical Analysis and Applications (23 papers), Analytical Chemistry and Sensors (14 papers) and Analytical chemistry methods development (13 papers). Jan Mocák is often cited by papers focused on Electrochemical Analysis and Applications (23 papers), Analytical Chemistry and Sensors (14 papers) and Analytical chemistry methods development (13 papers). Jan Mocák collaborates with scholars based in Slovakia, Czechia and Poland. Jan Mocák's co-authors include Alan M. Bond, Geoffrey R. Scollary, Stephen W. Feldberg, Andrzej Bobrowski, Michal Kirchner, Eva Matisová, Agnieszka Królicka, Kurt Kalcher, Karel Vytřas and Ivan Švancara and has published in prestigious journals such as Journal of the American Chemical Society, Analytical Chemistry and Food Chemistry.

In The Last Decade

Jan Mocák

65 papers receiving 1.6k citations

Hit Papers

A statistical overview of standard (IUPAC and ACS) and ne... 1997 2026 2006 2016 1997 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jan Mocák Slovakia 15 587 499 379 340 309 72 1.6k
Analytical Methods Committee 15 360 0.6× 399 0.8× 290 0.8× 492 1.4× 219 0.7× 87 2.0k
Franco Magno Italy 28 1.1k 1.9× 985 2.0× 515 1.4× 150 0.4× 316 1.0× 107 2.4k
Али Ниази Iran 27 676 1.2× 529 1.1× 333 0.9× 1.0k 3.1× 389 1.3× 153 2.5k
A. Gómez‐Hens Spain 25 193 0.3× 263 0.5× 324 0.9× 649 1.9× 408 1.3× 98 2.0k
Ziling Lu United States 17 346 0.6× 467 0.9× 466 1.2× 391 1.1× 277 0.9× 27 1.9k
A. Ruiz‐Medina Spain 29 341 0.6× 364 0.7× 364 1.0× 1.2k 3.5× 446 1.4× 121 2.7k
Paweł Kościelniak Poland 26 381 0.6× 353 0.7× 357 0.9× 1.2k 3.4× 673 2.2× 191 2.9k
L. Hernández Spain 29 1.4k 2.4× 1.5k 3.1× 1.0k 2.7× 417 1.2× 371 1.2× 153 2.8k
W.E. van der Linden Netherlands 26 838 1.4× 655 1.3× 900 2.4× 444 1.3× 677 2.2× 103 2.2k
J.M. Fernández-Romero Spain 21 145 0.2× 312 0.6× 178 0.5× 345 1.0× 456 1.5× 101 1.4k

Countries citing papers authored by Jan Mocák

Since Specialization
Citations

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

Fields of papers citing papers by Jan Mocák

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jan Mocák

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

All Works

20 of 20 papers shown
1.
Mocák, Jan, et al.. (2021). Computer-aided diagnosis of lung malignity using multidimensional analysis of tumour marker data. Nova Biotechnologica et Chimica. 8(1). 65–70.
2.
Bobrowski, A., et al.. (2015). METROLOGICAL CHARACTERISTICS AND COMPARISON OF ANALYTICAL METHODS FOR DETERMINATION OF CHROMIUM TRACES IN WATER SAMPLES. 3 indexed citations
3.
Mocák, Jan. (2012). Chemometrics in Medicine and Pharmacy. Nova Biotechnologica et Chimica. 11(1). 11–26. 11 indexed citations
4.
Bobrowski, Andrzej, et al.. (2010). ICP-OES Determination of Select Metals in Surface Water - a Metrological Study. Polish Journal of Environmental Studies. 19(1). 59–64. 11 indexed citations
5.
Mocák, Jan, et al.. (2010). Effect of the statin therapy on biochemical laboratory tests—A chemometrics study. Journal of Pharmaceutical and Biomedical Analysis. 54(1). 141–147. 6 indexed citations
6.
Mocák, Jan, et al.. (2009). Classification of white varietal wines using chemical analysis and sensorial evaluations. Acta chimica slovenica. 56(4). 765–772. 3 indexed citations
7.
Mocák, Jan, et al.. (2009). Use of multidimensional data analysis for prediction of lung malignity. Journal of Pharmaceutical and Biomedical Analysis. 50(2). 210–215. 6 indexed citations
8.
Matisová, Eva, et al.. (2009). Comparison of negative chemical ionization and electron impact ionization in gas chromatography–mass spectrometry of endocrine disrupting pesticides. Journal of Chromatography A. 1216(24). 4927–4932. 17 indexed citations
9.
Mocák, Jan, et al.. (2008). Classification and characterization of olive oils by UV-Vis absorption spectrometry and sensorial analysis. Journal of food and nutrition research. 47(4). 181–188. 18 indexed citations
10.
Mocák, Jan, et al.. (2008). ICP MS analysis and classification of potable, spring, and mineral waters. Chemical Papers. 62(5). 5 indexed citations
11.
Simonič, Marjana, et al.. (2007). Multivariate data analysis of natural mineral waters. Acta chimica slovenica. 54(1). 33–39. 8 indexed citations
12.
Kirchner, Michal, et al.. (2007). Fast gas chromatography for pesticide residues analysis using analyte protectants. Journal of Chromatography A. 1186(1-2). 271–280. 58 indexed citations
13.
Brandšteterová, E., et al.. (2006). HPLC determination of morphine, morphine-3-glucuronide and morphine-6-glucuronide in human serum of oncological patients after administration of morphine drugs.. PubMed. 61(6). 528–34. 7 indexed citations
14.
Mocák, Jan, et al.. (2006). Chemometric analysis of biochemical laboratory data of oncology patients after morphine treatment. Digitalni Knihovna (Univerzita Pardubice). 11. 315–330. 1 indexed citations
15.
Mocák, Jan, et al.. (2005). Correct ways of using regression for method comparison studies: Determination of LDL-cholesterol. Digitalni Knihovna (Univerzita Pardubice). 10. 119–129. 1 indexed citations
16.
Lankmayr, Ernst, et al.. (2004). Chemometrical classification of pumpkin seed oils using UV–Vis, NIR and FTIR spectra. Journal of Biochemical and Biophysical Methods. 61(1-2). 95–106. 43 indexed citations
17.
Mocák, Jan, et al.. (2002). Validation and Quality Assurance of Arsenic Determination in Urine by GFAAS after Toluene Extraction. Polish Journal of Environmental Studies. 11(6). 2 indexed citations
18.
Mocák, Jan & Andrzej Bobrowski. (2001). Determination of cadmium and lead in water - new recommended way of evaluating the limits of detection and quantification. Water Science & Technology Water Supply. 1(2). 19–26. 5 indexed citations
19.
Bustin, Dušan, Miroslav Rievaj, & Jan Mocák. (1978). Study of cyanoaquonitrosyl complexes of chromium. IV. Electrochemical reactions and complexation equilibria of the NO(H2O)4CrCN+ adducts with mercury(II). Inorganica Chimica Acta. 26. 11–16. 7 indexed citations
20.
Mocák, Jan, et al.. (1975). Coulometric titration of iodide and iodine with electrolytically generated hypobromite. Analytica Chimica Acta. 76(2). 433–442. 2 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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