Jil Daw

549 total citations
9 papers, 346 citations indexed

About

Jil Daw is a scholar working on Molecular Biology, Cardiology and Cardiovascular Medicine and Pathology and Forensic Medicine. According to data from OpenAlex, Jil Daw has authored 9 papers receiving a total of 346 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 3 papers in Cardiology and Cardiovascular Medicine and 2 papers in Pathology and Forensic Medicine. Recurrent topics in Jil Daw's work include Muscle Physiology and Disorders (3 papers), Viral Infections and Immunology Research (2 papers) and Prion Diseases and Protein Misfolding (2 papers). Jil Daw is often cited by papers focused on Muscle Physiology and Disorders (3 papers), Viral Infections and Immunology Research (2 papers) and Prion Diseases and Protein Misfolding (2 papers). Jil Daw collaborates with scholars based in United States, Spain and United Kingdom. Jil Daw's co-authors include A. Bowcock, Alan Menter, Derek Gordon, Cynthia Helms, Jürg Ott, Pui–Yan Kwok, Li Cao, Francesca Chamian, Ellen M. Wijsman and James G. Krueger and has published in prestigious journals such as Journal of Clinical Investigation, Nature Communications and Nature Genetics.

In The Last Decade

Jil Daw

7 papers receiving 337 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jil Daw United States	5	195	88	58	58	50	9	346
Bohdan P. Harvey United States	11	245 1.3×	107 1.2×	54 0.9×	33 0.6×	13 0.3×	20	411
Edith Graulich Germany	8	565 2.9×	98 1.1×	138 2.4×	22 0.4×	42 0.8×	9	678
J.A. van Roon Netherlands	8	160 0.8×	97 1.1×	75 1.3×	33 0.6×	98 2.0×	19	420
Teruhisa Otsuka Japan	10	133 0.7×	153 1.7×	100 1.7×	49 0.8×	78 1.6×	30	407
Elke Valk United Kingdom	10	378 1.9×	79 0.9×	177 3.1×	45 0.8×	17 0.3×	12	497
Katsushi Tokunaga Japan	13	248 1.3×	75 0.9×	26 0.4×	87 1.5×	24 0.5×	16	406
Joseph Dal Porto United States	7	541 2.8×	201 2.3×	71 1.2×	41 0.7×	28 0.6×	8	697
J G I van Rietschoten Netherlands	9	187 1.0×	223 2.5×	116 2.0×	29 0.5×	27 0.5×	11	481
Ty Brender United States	6	259 1.3×	61 0.7×	177 3.1×	41 0.7×	16 0.3×	9	375
H.P. Tony Germany	6	260 1.3×	72 0.8×	58 1.0×	20 0.3×	37 0.7×	10	368

Countries citing papers authored by Jil Daw

Since Specialization

Citations

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

Fields of papers citing papers by Jil Daw

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jil Daw

This figure shows the co-authorship network connecting the top 25 collaborators of Jil Daw. A scholar is included among the top collaborators of Jil Daw 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 Jil Daw. Jil Daw 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.

Inoue, Michio, Jil Daw, Sara K. Pittman, et al.. (2025). 690VPPathogenic chaperone-client networks underlie muscle protein aggregation: lessons from DNAJB4 myopathy. Neuromuscular Disorders. 53. 106000–106000.

2.

Robinson, Sarah, Andrew R. Findlay, Jil Daw, et al.. (2024). Elevated VCP ATPase Activity Correlates With Disease Onset in Multisystem Proteinopathy-1. Neurology Genetics. 10(5). e200191–e200191.

3.

Lynch, Eileen M., Sara K. Pittman, Jil Daw, et al.. (2024). Seeding-competent TDP-43 persists in human patient and mouse muscle. Science Translational Medicine. 16(775). eadp5730–eadp5730. 6 indexed citations

4.

Findlay, Andrew R., May M. Paing, Jil Daw, et al.. (2023). DNAJB6 isoform specific knockdown: Therapeutic potential for limb girdle muscular dystrophy D1. Molecular Therapy — Nucleic Acids. 32. 937–948. 4 indexed citations

5.

Li, Chengcheng, Sara K. Pittman, Jil Daw, et al.. (2023). Comprehensive functional characterization of SGCB coding variants predicts pathogenicity in limb-girdle muscular dystrophy type R4/2E. Journal of Clinical Investigation. 133(12). 5 indexed citations

6.

Rau, Michael, et al.. (2022). Disease-associated mutations within the yeast DNAJB6 homolog Sis1 slow conformer-specific substrate processing and can be corrected by the modulation of nucleotide exchange factors. Nature Communications. 13(1). 4570–4570. 2 indexed citations

7.

Lomonosova, Elena, et al.. (2017). Efficacy and cytotoxicity in cell culture of novel α-hydroxytropolone inhibitors of hepatitis B virus ribonuclease H. Antiviral Research. 144. 164–172. 39 indexed citations

8.

Helms, Cynthia, Nancy L. Saccone, Li Cao, et al.. (2005). Localization of PSORS1 to a haplotype block harboring HLA-C and distinct from corneodesmosin and HCR. Human Genetics. 118(3-4). 466–476. 53 indexed citations

9.

Helms, Cynthia, Li Cao, James G. Krueger, et al.. (2003). A putative RUNX1 binding site variant between SLC9A3R1 and NAT9 is associated with susceptibility to psoriasis. Nature Genetics. 35(4). 349–356. 237 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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