Thomas Lörch

533 total citations
17 papers, 416 citations indexed

About

Thomas Lörch is a scholar working on Molecular Biology, Genetics and Cancer Research. According to data from OpenAlex, Thomas Lörch has authored 17 papers receiving a total of 416 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 6 papers in Genetics and 4 papers in Cancer Research. Recurrent topics in Thomas Lörch's work include Genomic variations and chromosomal abnormalities (5 papers), Digital Imaging for Blood Diseases (3 papers) and AI in cancer detection (3 papers). Thomas Lörch is often cited by papers focused on Genomic variations and chromosomal abnormalities (5 papers), Digital Imaging for Blood Diseases (3 papers) and AI in cancer detection (3 papers). Thomas Lörch collaborates with scholars based in Germany, United States and Austria. Thomas Lörch's co-authors include Patrick Warnat, Nathalie Daigle, Christian Conrad, Rainer Pepperkok, Roland Eils, Jan Ellenberg, Holger Erfle, Peter F. Ambros, Karin M. Greulich‐Bode and Petra Boukamp and has published in prestigious journals such as Blood, Genome Research and Radiation Research.

In The Last Decade

Thomas Lörch

17 papers receiving 405 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Thomas Lörch Germany 10 228 139 61 58 51 17 416
Willem C.R. Sloos Netherlands 14 290 1.3× 88 0.6× 188 3.1× 43 0.7× 34 0.7× 21 517
Thierry Pécot United States 13 262 1.1× 67 0.5× 21 0.3× 100 1.7× 10 0.2× 34 502
Arthur Jones United States 7 267 1.2× 102 0.7× 49 0.8× 85 1.5× 21 0.4× 9 482
Duyen Ngo United States 10 257 1.1× 43 0.3× 62 1.0× 26 0.4× 36 0.7× 15 868
Magdalena Skalnı́ková Czechia 13 536 2.4× 64 0.5× 99 1.6× 36 0.6× 22 0.4× 22 626
Chana Rothmann Israel 11 158 0.7× 125 0.9× 19 0.3× 15 0.3× 10 0.2× 19 388
M. M. M. Pahlplatz Netherlands 12 158 0.7× 46 0.3× 21 0.3× 96 1.7× 8 0.2× 28 447
Brigit Greystoke United Kingdom 6 473 2.1× 23 0.2× 44 0.7× 36 0.6× 7 0.1× 9 698
Juho Konsti Finland 6 264 1.2× 58 0.4× 87 1.4× 94 1.6× 15 0.3× 9 551
Stanislav Stejskal Czechia 9 157 0.7× 67 0.5× 15 0.2× 10 0.2× 23 0.5× 17 265

Countries citing papers authored by Thomas Lörch

Since Specialization
Citations

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

Fields of papers citing papers by Thomas Lörch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Thomas Lörch

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

All Works

17 of 17 papers shown
1.
Schunck, Christian, et al.. (2023). A standardized and automated CBMN assay for biological dosimetry: the CytoRADx™ system. Radiation Protection Dosimetry. 199(14). 1516–1519. 1 indexed citations
2.
Pohlkamp, Christian, Niroshan Nadarajah, Piyush Srivastava, et al.. (2022). A Fully Automated Digital Workflow for Assessment of Bone Marrow Cytomorphology Based on Single Cell Detection and Classification with AI. Blood. 140(Supplement 1). 10725–10726. 3 indexed citations
3.
Lörch, Thomas, Michael Porter, Christopher L. Smith, et al.. (2021). CytoRADx: A High-Throughput, Standardized Biodosimetry Diagnostic System Based on the Cytokinesis-Block Micronucleus Assay. Radiation Research. 196(5). 523–534. 13 indexed citations
4.
Haferlach, Torsten, Christian Pohlkamp, Thomas Lörch, et al.. (2021). Automated Peripheral Blood Cell Differentiation Using Artificial Intelligence - a Study with More Than 10,000 Routine Samples in a Specialized Leukemia Laboratory. Blood. 138(Supplement 1). 103–103. 9 indexed citations
5.
Haferlach, Claudia, Wencke Walter, Melanie Zenger, et al.. (2020). Artificial Intelligence Substantially Supports Chromosome Banding Analysis Maintaining Its Strengths in Hematologic Diagnostics Even in the Era of Newer Technologies. Blood. 136(Supplement 1). 47–48. 10 indexed citations
6.
Pohlkamp, Christian, Niroshan Nadarajah, Thomas Lörch, et al.. (2020). Machine Learning (ML) Can Successfully Support Microscopic Differential Counts of Peripheral Blood Smears in a High Throughput Hematology Laboratory. Blood. 136(Supplement 1). 45–46. 6 indexed citations
7.
Brunner, Bodo, et al.. (2008). Sequence based high resolution chromosomal CGH. Cytogenetic and Genome Research. 121(1). 1–6. 3 indexed citations
8.
Bozsaky, Eva, Dietmar Rieder, Gabriela Bindea, et al.. (2007). A new platform linking chromosomal and sequence information. Chromosome Research. 15(3). 327–39. 6 indexed citations
9.
Kajtár, Béla, et al.. (2006). Automated fluorescent in situ hybridization (FISH) analysis of t(9;22)(q34;q11) in interphase nuclei. Cytometry Part A. 69A(6). 506–514. 37 indexed citations
10.
Lörch, Thomas, et al.. (2005). Automatic telomere length measurements in interphase nuclei by IQ‐FISH. Cytometry Part A. 68A(2). 113–120. 41 indexed citations
11.
Christensen, Britta, John Philip, Steen Kølvraa, et al.. (2005). Fetal Cells in Maternal Blood: A Comparison of Methods for Cell Isolation and Identification. Fetal Diagnosis and Therapy. 20(2). 106–112. 15 indexed citations
12.
Conrad, Christian, Holger Erfle, Patrick Warnat, et al.. (2004). Automatic Identification of Subcellular Phenotypes on Human Cell Arrays. Genome Research. 14(6). 1130–1136. 166 indexed citations
13.
Christensen, Brian, Steen Kølvraa, Thomas Lörch, et al.. (2003). Studies on the Isolation and Identification of Fetal Nucleated Red Blood Cells in the Circulation of Pregnant Women before and after Chorion Villus Sampling. Fetal Diagnosis and Therapy. 18(5). 376–384. 19 indexed citations
14.
Lörch, Thomas, et al.. (2003). Automatic quantification of gene amplification in clinical samples by IQ‐FISH. Cytometry Part B Clinical Cytometry. 57B(1). 15–22. 15 indexed citations
15.
Karhu, Ritva, Jaana Rummukainen, Thomas Lörch, & Jorma Isola. (1999). Four‐color CGH: A new method for quality control of comparative genomic hybridization. Genes Chromosomes and Cancer. 24(2). 112–118. 1 indexed citations
16.
Zitzelsberger, Horst, Ulrike Kulka, Axel Walch, et al.. (1998). Genetic heterogeneity in a prostatic carcinoma and associated prostatic intraepithelial neoplasia as demonstrated by combined use of laser-microdissection, degenerate oligonucleotide primed PCR and comparative genomic hybridization. Archiv für Pathologische Anatomie und Physiologie und für Klinische Medicin. 433(4). 297–304. 60 indexed citations
17.
Merkle, Fritz & Thomas Lörch. (1984). Hybrid optical–digital pattern recognition. Applied Optics. 23(10). 1509–1509. 11 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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