Ute Bach

691 total citations
9 papers, 252 citations indexed

About

Ute Bach is a scholar working on Molecular Biology, Oncology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Ute Bach has authored 9 papers receiving a total of 252 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Molecular Biology, 3 papers in Oncology and 2 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Ute Bach's work include Immunotoxicology and immune responses (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper) and Amino Acid Enzymes and Metabolism (1 paper). Ute Bach is often cited by papers focused on Immunotoxicology and immune responses (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper) and Amino Acid Enzymes and Metabolism (1 paper). Ute Bach collaborates with scholars based in Germany, United States and Switzerland. Ute Bach's co-authors include Bernhard Dobberstein, Darlene Dixon, Eric van Esch, Midori Yoshida, Michael Mirsky, Johannes H. Harleman, George L. Foley, Roger Alison, Karyn Colman and Ronald Herbert and has published in prestigious journals such as Journal of Biological Chemistry, Experimental Cell Research and Toxicologic Pathology.

In The Last Decade

Ute Bach

7 papers receiving 245 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ute Bach Germany	7	96	55	47	36	29	9	252
Letizia Paladino Italy	10	231 2.4×	51 0.9×	9 0.2×	14 0.4×	11 0.4×	23	354
Shizhi Wang China	9	139 1.4×	15 0.3×	32 0.7×	26 0.7×	13 0.4×	24	380
Ramy Elgendy Sweden	10	143 1.5×	29 0.5×	14 0.3×	25 0.7×	9 0.3×	24	280
Ildikó Erdélyi United States	8	138 1.4×	32 0.6×	6 0.1×	92 2.6×	49 1.7×	10	377
Chengcheng Xu China	14	148 1.5×	99 1.8×	7 0.1×	49 1.4×	8 0.3×	29	376
Christoph Lengger Germany	7	120 1.3×	16 0.3×	31 0.7×	14 0.4×	8 0.3×	9	248
Mylène Blais Canada	13	278 2.9×	52 0.9×	35 0.7×	65 1.8×	2 0.1×	18	466
Xuhui Feng China	8	167 1.7×	104 1.9×	14 0.3×	59 1.6×	7 0.2×	15	397
Yan-Jun Hu China	8	114 1.2×	35 0.6×	2 0.0×	24 0.7×	16 0.6×	12	324
Xiaoping Li China	11	131 1.4×	81 1.5×	20 0.4×	12 0.3×	14 0.5×	28	395

Countries citing papers authored by Ute Bach

Since Specialization

Citations

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

Fields of papers citing papers by Ute Bach

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ute Bach

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

9 of 9 papers shown

1.

Bach, Ute, et al.. (2024). Latent Diffusion Models with Image-Derived Annotations for Enhanced AI-Assisted Cancer Diagnosis in Histopathology. Diagnostics. 14(13). 1442–1442. 7 indexed citations

2.

Schafer, Kenneth A., Ute Bach, Joshua T. Bartoe, et al.. (2024). International Harmonization of Nomenclature and Diagnostic Criteria (INHAND): Nonproliferative and Proliferative Lesions of Nonrodent Ocular Tissues. Toxicologic Pathology. 52(7). 368–455.

3.

Grevot, Armelle, Julie Boisclair, Magali Guffroy, et al.. (2023). Toxicologic Pathology Forum Opinion Piece: Use of Virtual Control Groups in Nonclinical Toxicity Studies: The Anatomic Pathology Perspective. Toxicologic Pathology. 51(6). 390–396.

4.

Ramos, Meg Ferrell, Ute Bach, Jacqueline Brassard, et al.. (2018). Nonproliferative and Proliferative Lesions of the Ratand Mouse Special Sense Organs(Ocular [eye and glands], Olfactory and Otic). Journal of Toxicologic Pathology. 31(3_Suppl). 97S–214S. 30 indexed citations

5.

Dixon, Darlene, Roger Alison, Ute Bach, et al.. (2014). Nonproliferative and Proliferative Lesions of the Rat and Mouse Female Reproductive System. Journal of Toxicologic Pathology. 27(3+4_Suppl). 1S–107S. 108 indexed citations

6.

Bach, Ute, James R. Hailey, Wolfgang Kaufmann, et al.. (2009). Proceedings of the 2009 National Toxicology Program Satellite Symposium. Toxicologic Pathology. 38(1). 9–36. 14 indexed citations

7.

Bach, Ute, et al.. (2003). Parasitological and morphological findings in porcine isosporosis after treatment with symmetrical triazintriones. Parasitology Research. 91(1). 27–33. 24 indexed citations

8.

Bach, Ute, et al.. (2001). Prion Protein Contains a Second Endoplasmic Reticulum Targeting Signal Sequence Located at Its C Terminus. Journal of Biological Chemistry. 276(16). 13388–13394. 42 indexed citations

9.

Bach, Ute, Markus Baiersdörfer, Gerd Klöck, et al.. (2001). Apoptotic Cell Debris and Phosphatidylserine-Containing Lipid Vesicles Induce Apolipoprotein J (Clusterin) Gene Expression in Vital Fibroblasts. Experimental Cell Research. 265(1). 11–20. 27 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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