Sameena S. Khan

1.1k total citations
9 papers, 857 citations indexed

About

Sameena S. Khan is a scholar working on Immunology, Molecular Biology and Oncology. According to data from OpenAlex, Sameena S. Khan has authored 9 papers receiving a total of 857 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Immunology, 2 papers in Molecular Biology and 2 papers in Oncology. Recurrent topics in Sameena S. Khan's work include Immune Cell Function and Interaction (4 papers), T-cell and B-cell Immunology (3 papers) and Immune Response and Inflammation (2 papers). Sameena S. Khan is often cited by papers focused on Immune Cell Function and Interaction (4 papers), T-cell and B-cell Immunology (3 papers) and Immune Response and Inflammation (2 papers). Sameena S. Khan collaborates with scholars based in United States, India and Ireland. Sameena S. Khan's co-authors include J. Philip McCoy, Michael A. Solomon, Debra Reda, Anthony F. Suffredini, J. Philip McCoy, Mohamed F. Elshal, Yoshiyuki Takahashi, Peter J. Munson, Robert L. Danner and Jennifer J. Barb and has published in prestigious journals such as SHILAP Revista de lepidopterología, Blood and Transfusion.

In The Last Decade

Sameena S. Khan

8 papers receiving 843 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Sameena S. Khan United States	7	410	233	207	115	92	9	857
Bin Jiang China	15	386 0.9×	210 0.9×	142 0.7×	114 1.0×	102 1.1×	80	965
Isabelle Allaeys Canada	17	537 1.3×	294 1.3×	182 0.9×	90 0.8×	76 0.8×	32	1.2k
Jin Zhou China	19	262 0.6×	299 1.3×	163 0.8×	136 1.2×	149 1.6×	53	1.0k
Peter H. Lapchak United States	18	308 0.8×	404 1.7×	193 0.9×	132 1.1×	55 0.6×	29	972
Chia Chi Sun United States	12	369 0.9×	236 1.0×	352 1.7×	181 1.6×	75 0.8×	13	1.7k
Clemens Feistritzer Austria	19	327 0.8×	189 0.8×	139 0.7×	119 1.0×	95 1.0×	51	976
Jens Gerwien Denmark	17	295 0.7×	448 1.9×	173 0.8×	110 1.0×	53 0.6×	33	1.1k
John Chapin United States	14	260 0.6×	151 0.6×	118 0.6×	87 0.8×	143 1.6×	26	1.2k
Valerie A. Novakovic United States	22	420 1.0×	396 1.7×	95 0.5×	123 1.1×	130 1.4×	46	1.2k
Gaurav Kumar United States	16	223 0.5×	266 1.1×	136 0.7×	91 0.8×	68 0.7×	48	790

Countries citing papers authored by Sameena S. Khan

Since Specialization

Citations

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

Fields of papers citing papers by Sameena S. Khan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sameena S. Khan. 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 Sameena S. Khan. The network helps show where Sameena S. Khan may publish in the future.

Co-authorship network of co-authors of Sameena S. Khan

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

All Works

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9 of 9 papers shown

Khan, Sameena S., et al.. (2021). Herd immunity. SHILAP Revista de lepidopterología. 10(9). 3522–3523. 2 indexed citations

Khan, Sameena S., et al.. (2021). New Zealand in Snap Lockdown. Was it Not Inevitable. SHILAP Revista de lepidopterología. 15(Suppl 1). S132–S133.

Solomon, Steven B., Irene Cortés‐Puch, Junfeng Sun, et al.. (2015). Transfused older stored red blood cells improve the clinical course and outcome in a canine lethal hemorrhage and reperfusion model. Transfusion. 55(11). 2552–2563. 14 indexed citations

Khan, Sameena S., Deborah J. Burt, Christy Ralph, et al.. (2010). Tremelimumab (anti-CTLA4) mediates immune responses mainly by direct activation of T effector cells rather than by affecting T regulatory cells. Clinical Immunology. 138(1). 85–96. 57 indexed citations

Elshal, Mohamed F., Sameena S. Khan, Nalini Raghavachari, et al.. (2007). A unique population of effector memory lymphocytes identified by CD146 having a distinct immunophenotypic and genomic profile. BMC Immunology. 8(1). 29–29. 44 indexed citations

Talwar, Shefali, Peter J. Munson, Jennifer J. Barb, et al.. (2006). Gene expression profiles of peripheral blood leukocytes after endotoxin challenge in humans. Physiological Genomics. 25(2). 203–215. 100 indexed citations

Khan, Sameena S., Michael A. Solomon, & J. Philip McCoy. (2005). Detection of circulating endothelial cells and endothelial progenitor cells by flow cytometry. Cytometry Part B Clinical Cytometry. 64B(1). 1–8. 260 indexed citations

Elshal, Mohamed F., Sameena S. Khan, Yoshiyuki Takahashi, Michael A. Solomon, & J. Philip McCoy. (2005). CD146 (Mel-CAM), an adhesion marker of endothelial cells, is a novel marker of lymphocyte subset activation in normal peripheral blood. Blood. 106(8). 2923–2924. 88 indexed citations

Khan, Sameena S., et al.. (2004). Multiplex bead array assays for detection of soluble cytokines: Comparisons of sensitivity and quantitative values among kits from multiple manufacturers. Cytometry Part B Clinical Cytometry. 61B(1). 35–39. 292 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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