Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
The SCID-hu Mouse: Murine Model for the Analysis of Human Hematolymphoid Differentiation and Function
19881.1k citationsJ M McCune, Reiko Namikawa et al.Scienceprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of L D Shultz'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 L D Shultz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites L D Shultz more than expected).
This network shows the impact of papers produced by L D Shultz. 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 L D Shultz. The network helps show where L D Shultz may publish in the future.
Co-authorship network of co-authors of L D Shultz
This figure shows the co-authorship network connecting the top 25 collaborators of L D Shultz.
A scholar is included among the top collaborators of L D Shultz 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 L D Shultz. L D Shultz is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Ramı́rez, Manuel, et al.. (1998). Mature human hematopoietic cells in donor bone marrow complicate interpretation of stem/progenitor cell assays in xenogeneic hematopoietic chimeras.. PubMed. 26(4). 332–44.45 indexed citations
Umeda, Shigeaki, Kei Takahashi, Munekazu Naito, L D Shultz, & Katsumasa Takagi. (1996). Neonatal changes of osteoclasts in osteopetrosis (op/op) mice defective in production of functional macrophage colony-stimulating factor (M-CSF) protein and effects of M-CSF on osteoclast development and differentiation.. PubMed. 28(1). 13–26.25 indexed citations
Blazar, Bruce R., Catherine A. Brennan, H E Broxmeyer, L D Shultz, & Daniel A. Vallera. (1995). Transgenic mice expressing either bovine growth hormone (bGH) or human GH releasing hormone (hGRH) have increased splenic progenitor cell colony formation and DNA synthesis in vitro and in vivo.. PubMed. 23(13). 1397–406.25 indexed citations
12.
Welsh, Raymond M., Carey L. O’Donnell, & L D Shultz. (1995). Antiviral activity of NK 1.1+ natural killer cells in C57BL/6 scid mice infected with murine cytomegalovirus.. PubMed. 13(5). 239–45.29 indexed citations
13.
Haar, Jack L., J. Popp, & L D Shultz. (1989). Defective in vitro migratory capacity of bone marrow cells from viable motheaten mice in response to normal thymus culture supernatants.. PubMed. 17(1). 21–4.6 indexed citations
14.
McCune, J M, Reiko Namikawa, Hideto Kaneshima, et al.. (1988). The SCID-hu Mouse: Murine Model for the Analysis of Human Hematolymphoid Differentiation and Function. Science. 241(4873). 1632–1639.1135 indexed citations breakdown →
Shultz, L D, Dale Rex Coman, Charles Bailey, Wesley G. Beamer, & C L Sidman. (1984). "Viable motheaten," a new allele at the motheaten locus. I. Pathology.. PubMed. 116(2). 179–92.180 indexed citations
Shultz, L D, Charles Bailey, & Daniel Coman. (1983). Hematopoietic stem cell function in motheaten mice.. PubMed. 11(7). 667–80.23 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.