Khaja Syed

1.6k total citations · 1 hit paper
15 papers, 1.1k citations indexed

About

Khaja Syed is a scholar working on Hematology, Immunology and Molecular Biology. According to data from OpenAlex, Khaja Syed has authored 15 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Hematology, 5 papers in Immunology and 4 papers in Molecular Biology. Recurrent topics in Khaja Syed's work include Acute Myeloid Leukemia Research (4 papers), Spectroscopy Techniques in Biomedical and Chemical Research (4 papers) and Immune Cell Function and Interaction (3 papers). Khaja Syed is often cited by papers focused on Acute Myeloid Leukemia Research (4 papers), Spectroscopy Techniques in Biomedical and Chemical Research (4 papers) and Immune Cell Function and Interaction (3 papers). Khaja Syed collaborates with scholars based in United States, United Kingdom and Netherlands. Khaja Syed's co-authors include Inger S. Nijhof, Tuna Mutis, Niels W.C.J. van de Donk, Tineke Casneuf, A. Kate Sasser, Henk M. Lokhorst, Tahamtan Ahmadi, Brendan M. Weiss, Jakub Krejcik and Torben Plesner and has published in prestigious journals such as Blood, International Journal of Cancer and The Analyst.

In The Last Decade

Khaja Syed

14 papers receiving 1.0k citations

Hit Papers

align trajectories

What are hit papers?

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.

Daratumumab depletes CD38+ immune regulatory cells, promotes T-cell expansion, and skews T-cell repertoire in multiple myeloma

2016 649 citations Jakub Krejcik, Tineke Casneuf et al. Blood profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Khaja Syed United States	8	635	524	376	311	195	15	1.1k
Mattia D’Agostino Italy	15	439 0.7×	482 0.9×	451 1.2×	137 0.4×	87 0.4×	43	861
Antonia Cagnetta Italy	13	597 0.9×	612 1.2×	607 1.6×	168 0.5×	219 1.1×	38	1.2k
Hans Skvara Austria	12	126 0.2×	255 0.5×	270 0.7×	160 0.5×	23 0.1×	22	771
Aleksandra Wroblewska Netherlands	12	205 0.3×	163 0.3×	255 0.7×	131 0.4×	95 0.5×	17	606
Mike Zhong China	6	516 0.8×	566 1.1×	357 0.9×	206 0.7×	233 1.2×	21	881
Guangchun Song United States	15	894 1.4×	216 0.4×	913 2.4×	185 0.6×	10 0.1×	26	1.7k
Nikesh Kotecha United States	7	223 0.4×	191 0.4×	564 1.5×	299 1.0×	22 0.1×	13	990
Antreas Hindoyan United States	11	125 0.2×	365 0.7×	409 1.1×	114 0.4×	48 0.2×	24	767
Michele S. Redell United States	18	315 0.5×	402 0.8×	562 1.5×	203 0.7×	48 0.2×	50	1.1k
Mika Kontro Finland	13	423 0.7×	156 0.3×	505 1.3×	77 0.2×	20 0.1×	53	903

Countries citing papers authored by Khaja Syed

Since Specialization

Citations

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

Fields of papers citing papers by Khaja Syed

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Khaja Syed

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

All Works

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15 of 15 papers shown

Theakstone, Ashton G., Paul M. Brennan, Michael D. Jenkinson, et al.. (2021). Rapid Spectroscopic Liquid Biopsy for the Universal Detection of Brain Tumours. Cancers. 13(15). 3851–3851. 25 indexed citations

Saeed, Farhan, et al.. (2021). Body Image Dissatisfaction in Healthy Medical Students and its Association to Body Mass Index, Gender and Age. Annals of King Edward Medical University. 27(1). 15–23.

Cameron, James M., Christopher Rinaldi, Holly J. Butler, et al.. (2020). Stratifying Brain Tumour Histological Sub-Types: The Application of ATR-FTIR Serum Spectroscopy in Secondary Care. Cancers. 12(7). 1710–1710. 27 indexed citations

Cameron, James M., Christopher Rinaldi, Alexandra Sala, et al.. (2020). Interrogation of IDH1 Status in Gliomas by Fourier Transform Infrared Spectroscopy. Cancers. 12(12). 3682–3682. 10 indexed citations

Syed, Khaja, et al.. (2020). Novel combinations to improve hematopoiesis in myelodysplastic syndrome. Stem Cell Research & Therapy. 11(1). 132–132. 6 indexed citations

Das, Kumar, et al.. (2020). Differentiating Nonenhancing Grade II Gliomas from Grade III Gliomas Using Diffusion Tensor Imaging and Dynamic Susceptibility Contrast MRI. World Neurosurgery. 146. e555–e564. 2 indexed citations

Cameron, James M., Holly J. Butler, Benjamin R. Smith, et al.. (2019). Developing infrared spectroscopic detection for stratifying brain tumour patients: glioblastoma multiforme vs. lymphoma. The Analyst. 144(22). 6736–6750. 35 indexed citations

Riether, Carsten, Amy J. Johnson, Christina D. Drenberg, et al.. (2019). The Combination of the BCL-2 Antagonist Venetoclax with the CD70-Targeting Antibody Cusatuzumab Synergistically Eliminates Primary Human Leukemia Stem Cells. Blood. 134(Supplement_1). 3918–3918. 5 indexed citations

Droop, Alastair, Alexander Bruns, Georgette Tanner, et al.. (2017). How to analyse the spatiotemporal tumour samples needed to investigate cancer evolution: A case study using paired primary and recurrent glioblastoma. International Journal of Cancer. 142(8). 1620–1626. 3 indexed citations

10.

Nijhof, Inger S., Tineke Casneuf, Berris van Kessel, et al.. (2016). CD38 expression and complement inhibitors affect response and resistance to daratumumab therapy in myeloma. Blood. 128(7). 959–970. 275 indexed citations

11.

Krejcik, Jakub, Tineke Casneuf, Inger S. Nijhof, et al.. (2016). Daratumumab depletes CD38+ immune regulatory cells, promotes T-cell expansion, and skews T-cell repertoire in multiple myeloma. Blood. 128(3). 384–394. 649 indexed citations breakdown →

12.

Forslund, Ann, Khaja Syed, Amy Axel, et al.. (2016). Ex Vivo Activity Profile of the CD123xCD3 Duobody® Antibody JNJ-63709178 Against Primary Acute Myeloid Leukemia Bone Marrow Samples. Blood. 128(22). 2875–2875. 3 indexed citations

13.

Syed, Khaja, et al.. (2015). Preclinical Evaluation of CSL362/JNJ-56022473 in Combination with Decitabine or Azacitidine in in Vitro Assays. Blood. 126(23). 1370–1370. 7 indexed citations

14.

Syed, Khaja, et al.. (2015). Preclinical Evaluation of CSL362/JNJ-56022473 Single Agent in in Vitro Assays. Blood. 126(23). 4946–4946. 3 indexed citations

15.

Syed, Khaja, et al.. (2014). Effects of Ibrutinib on Rituximab and GA-101 Induced Antibody-Dependent Cell Cytotoxicity (ADCC) in Lymphoma Cells in Vitro. Blood. 124(21). 3117–3117. 7 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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