Daniel Wolf

4.1k total citations · 2 hit papers
35 papers, 3.1k citations indexed

About

Daniel Wolf is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging and Cellular and Molecular Neuroscience. According to data from OpenAlex, Daniel Wolf has authored 35 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 8 papers in Radiology, Nuclear Medicine and Imaging and 6 papers in Cellular and Molecular Neuroscience. Recurrent topics in Daniel Wolf's work include Radiomics and Machine Learning in Medical Imaging (7 papers), HIV Research and Treatment (6 papers) and Virus-based gene therapy research (4 papers). Daniel Wolf is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (7 papers), HIV Research and Treatment (6 papers) and Virus-based gene therapy research (4 papers). Daniel Wolf collaborates with scholars based in United States, Germany and United Kingdom. Daniel Wolf's co-authors include Stephen P. Goff, Tony Kouzarides, Adrian Bird, Paul J. Hurd, Xinsheng Nan, François Fuks, Shane Grealish, Malin Parmar, Martin Lundblad and James Wood and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Daniel Wolf

33 papers receiving 3.0k citations

Hit Papers

The Methyl-CpG-binding Protein MeCP2 Links DNA Methylatio... 2003 2026 2010 2018 2003 2012 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
Daniel Wolf United States 21 2.3k 607 485 317 290 35 3.1k
Pablo Pérez‐Piñera United States 35 3.5k 1.5× 694 1.1× 398 0.8× 278 0.9× 60 0.2× 78 4.5k
Paul Le Tissier United Kingdom 27 1.3k 0.6× 827 1.4× 159 0.3× 237 0.7× 68 0.2× 59 2.9k
Lyle W. Ostrow United States 18 1.4k 0.6× 179 0.3× 468 1.0× 299 0.9× 153 0.5× 33 2.8k
Patrick Salmon Switzerland 32 2.2k 1.0× 1.0k 1.7× 259 0.5× 54 0.2× 160 0.6× 60 3.9k
Concepción Rodrı́guez Esteban United States 34 4.0k 1.8× 749 1.2× 165 0.3× 114 0.4× 62 0.2× 48 4.9k
Ajamete Kaykas United States 21 3.9k 1.7× 746 1.2× 472 1.0× 71 0.2× 153 0.5× 27 5.2k
Paul G. Giresi United States 20 6.1k 2.6× 1.2k 1.9× 262 0.5× 760 2.4× 138 0.5× 26 7.4k
Weizhi Ji China 33 2.1k 0.9× 609 1.0× 166 0.3× 97 0.3× 167 0.6× 142 3.7k
Manching Ku United States 25 7.8k 3.4× 1.3k 2.2× 392 0.8× 371 1.2× 293 1.0× 33 8.8k

Countries citing papers authored by Daniel Wolf

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Wolf

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Wolf

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Wolf. A scholar is included among the top collaborators of Daniel Wolf 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 Daniel Wolf. Daniel Wolf 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
3.
Rifes, Pedro, Janko Kajtez, Gaurav Rathore, et al.. (2024). Forced LMX1A expression induces dorsal neural fates and disrupts patterning of human embryonic stem cells into ventral midbrain dopaminergic neurons. Stem Cell Reports. 19(6). 830–838. 2 indexed citations
4.
Sollmann, Nico, et al.. (2023). Sarcopenia – Definition, Radiological Diagnosis, Clinical Significance. RöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren. 195(5). 393–405. 30 indexed citations
5.
Wolf, Daniel, Stefan Schmidt, Meinrad Beer, et al.. (2023). Radiomics and Clinicopathological Characteristics for Predicting Lymph Node Metastasis in Testicular Cancer. Cancers. 15(23). 5630–5630. 4 indexed citations
6.
Kitto, Kelley F., Harsha Verma, Daniel J. Schuster, et al.. (2023). Long-term reversal of chronic pain behavior in rodents through elevation of spinal agmatine. Molecular Therapy. 31(4). 1123–1135. 7 indexed citations
7.
8.
Wolf, Daniel, et al.. (2023). CT Radiomics and Clinical Feature Model to Predict Lymph Node Metastases in Early-Stage Testicular Cancer. SHILAP Revista de lepidopterología. 3(2). 65–80. 3 indexed citations
9.
Wolf, Daniel, Sebastian Regnery, R. Tarnawski, et al.. (2022). Weakly Supervised Learning with Positive and Unlabeled Data for Automatic Brain Tumor Segmentation. Applied Sciences. 12(21). 10763–10763. 7 indexed citations
10.
Wolf, Daniel, Stefan Schmidt, Wolfgang Thaiss, et al.. (2022). Deep Neural Networks and Machine Learning Radiomics Modelling for Prediction of Relapse in Mantle Cell Lymphoma. Cancers. 14(8). 2008–2008. 20 indexed citations
11.
Sullivan‐Stack, Jenna, Curt Mazur, Daniel Wolf, et al.. (2020). Convective forces increase rostral delivery of intrathecal radiotracers and antisense oligonucleotides in the cynomolgus monkey nervous system. Journal of Translational Medicine. 18(1). 309–309. 28 indexed citations
12.
Swayze, Eric E., Berit Powers, Fredrik Kamme, et al.. (2016). Kinetics of ASO Distribution and Pharmacodynamics in the CNS after an Intrathecal Bolus Dose in Rat (S38.008). Neurology. 86(16_supplement). 1 indexed citations
13.
Wolf, Daniel, Jenna Sullivan‐Stack, Curt Mazur, et al.. (2016). The Effect of Bolus Volume and Mechanical Forces on the Biodistribution of ASOs Following Lumbar Intrathecal Administration in Cynomolgus Monkeys (S38.007). Neurology. 86(16_supplement). 3 indexed citations
14.
Wolf, Daniel, et al.. (2014). Gene therapy for neurologic manifestations of mucopolysaccharidoses. Expert Opinion on Drug Delivery. 12(2). 283–296. 35 indexed citations
15.
Kirkeby, Agnete, Shane Grealish, Daniel Wolf, et al.. (2012). Generation of Regionally Specified Neural Progenitors and Functional Neurons from Human Embryonic Stem Cells under Defined Conditions. Cell Reports. 1(6). 703–714. 494 indexed citations breakdown →
16.
Wolf, Daniel, Leah R. Hanson, Elena L. Aronovich, et al.. (2012). Lysosomal enzyme can bypass the blood–brain barrier and reach the CNS following intranasal administration. Molecular Genetics and Metabolism. 106(1). 131–134. 49 indexed citations
17.
Ooi, Steen K.T., Daniel Wolf, Odelya Hartung, et al.. (2010). Dynamic instability of genomic methylation patterns in pluripotent stem cells. Epigenetics & Chromatin. 3(1). 17–17. 77 indexed citations
18.
Wolf, Daniel & Stephen P. Goff. (2009). Embryonic stem cells use ZFP809 to silence retroviral DNAs. Nature. 458(7242). 1201–1204. 293 indexed citations
19.
Fuks, François, Paul J. Hurd, Daniel Wolf, et al.. (2003). The Methyl-CpG-binding Protein MeCP2 Links DNA Methylation to Histone Methylation. Journal of Biological Chemistry. 278(6). 4035–4040. 768 indexed citations breakdown →
20.
Wolf, Daniel, Marianna Rodova, Eric A. Miska, James P. Calvet, & Tony Kouzarides. (2002). Acetylation of β-Catenin by CREB-binding Protein (CBP). Journal of Biological Chemistry. 277(28). 25562–25567. 144 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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