Elizabeth Nacheva

556 total citations
16 papers, 410 citations indexed

About

Elizabeth Nacheva is a scholar working on Genetics, Molecular Biology and Genetics. According to data from OpenAlex, Elizabeth Nacheva has authored 16 papers receiving a total of 410 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Genetics, 7 papers in Molecular Biology and 7 papers in Genetics. Recurrent topics in Elizabeth Nacheva's work include Genomic variations and chromosomal abnormalities (7 papers), Chronic Lymphocytic Leukemia Research (5 papers) and Chronic Myeloid Leukemia Treatments (5 papers). Elizabeth Nacheva is often cited by papers focused on Genomic variations and chromosomal abnormalities (7 papers), Chronic Lymphocytic Leukemia Research (5 papers) and Chronic Myeloid Leukemia Treatments (5 papers). Elizabeth Nacheva collaborates with scholars based in United Kingdom, United States and France. Elizabeth Nacheva's co-authors include Colin Grace, Susan Gribble, Ian Roberts, Maria Łastowska, Ann Curtis, Andrew D.J. Pearson, Nick Bown, Anthony R. Green, Henry Houlden and Christos Proukakis and has published in prestigious journals such as Blood, PLoS ONE and Brain.

In The Last Decade

Elizabeth Nacheva

15 papers receiving 404 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Elizabeth Nacheva United Kingdom	11	161	130	124	108	99	16	410
Raffaella Defferrari Italy	13	157 1.0×	196 1.5×	157 1.3×	111 1.0×	44 0.4×	27	455
Jeff Jorgensen United States	4	111 0.7×	95 0.7×	68 0.5×	37 0.3×	47 0.5×	6	313
Lynn Greenhalgh United Kingdom	8	226 1.4×	29 0.2×	61 0.5×	62 0.6×	181 1.8×	11	507
Marta Byrska-Bishop United States	8	212 1.3×	53 0.4×	70 0.6×	85 0.8×	56 0.6×	9	379
Lauren A. Solomon Canada	14	260 1.6×	53 0.4×	21 0.2×	91 0.8×	65 0.7×	22	483
Yinyan Xu China	10	191 1.2×	75 0.6×	108 0.9×	88 0.8×	10 0.1×	31	382
Szymon Janczar Poland	10	188 1.2×	29 0.2×	36 0.3×	29 0.3×	101 1.0×	29	338
Astrid Nümann Germany	10	223 1.4×	181 1.4×	13 0.1×	94 0.9×	84 0.8×	13	469
Sonia Alonso‐Martín Spain	13	382 2.4×	30 0.2×	43 0.3×	105 1.0×	75 0.8×	26	521
Donna C. Rich United States	7	260 1.6×	241 1.9×	15 0.1×	34 0.3×	176 1.8×	8	580

Countries citing papers authored by Elizabeth Nacheva

Since Specialization

Citations

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

Fields of papers citing papers by Elizabeth Nacheva

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Elizabeth Nacheva

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

All Works

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16 of 16 papers shown

1.

Taanman, Jan‐Willem, Tammaryn Lashley, Helen Ling, et al.. (2018). Somatic copy number gains of α-synuclein (SNCA) in Parkinson’s disease and multiple system atrophy brains. Brain. 141(8). 2419–2431. 53 indexed citations

2.

Nacheva, Elizabeth, Alan Pittman, Colin Grace, et al.. (2017). DNA isolation protocol effects on nuclear DNA analysis by microarrays, droplet digital PCR, and whole genome sequencing, and on mitochondrial DNA copy number estimation. PLoS ONE. 12(7). e0180467–e0180467. 23 indexed citations

3.

Kara, Eleanna, Aoife P. Kiely, Christos Proukakis, et al.. (2014). A 6.4 Mb Duplication of the α-Synuclein Locus Causing Frontotemporal Dementia and Parkinsonism. JAMA Neurology. 71(9). 1162–1162. 54 indexed citations

4.

Prince, H. Miles, Paul Turner, Colin Grace, et al.. (2008). chronic myeloid leukemia translocation and provide a powerful and independent prognostic indicator in Deletions of the derivative chromosome 9 occur at the time of the Philadelphia.

5.

Song, Lynda L., Andrei Zlobin, Pushpankur Ghoshal, et al.. (2005). Alteration of SMRT Tumor Suppressor Function in Transformed Non-Hodgkin Lymphomas. Cancer Research. 65(11). 4554–4561. 15 indexed citations

6.

Duin, Mark van, Ronald van Marion, J. E. Vivienne Watson, et al.. (2004). Construction and application of a full‐coverage, high‐resolution, human chromosome 8q genomic microarray for comparative genomic hybridization. Cytometry Part A. 63A(1). 10–19. 16 indexed citations

7.

Gribble, Susan, Alistair Reid, Ian Roberts, et al.. (2003). Genomic imbalances in CML blast crisis: 8q24.12–q24.13 Segment identified as a common region of over‐representation. Genes Chromosomes and Cancer. 37(4). 346–358. 15 indexed citations

8.

Huntly, Brian J.P., Anthony J. Bench, Éric Delabesse, et al.. (2002). Derivative chromosome 9 deletions in chronic myeloid leukemia: poor prognosis is not associated with loss of ABL-BCRexpression, elevated BCR-ABL levels, or karyotypic instability. Blood. 99(12). 4547–4553. 66 indexed citations

9.

Gribble, Susan, et al.. (2000). Cytogenetics of the Chronic Myeloid Leukemia-Derived Cell Line K562. Cancer Genetics and Cytogenetics. 118(1). 1–8. 48 indexed citations

10.

Pearson, Thomas C., M. Messinezy, Nigel Westwood, et al.. (2000). A Polycythemia Vera Update: Diagnosis, Pathobiology, and Treatment. Hematology. 2000(1). 51–68. 7 indexed citations

11.

Pearson, Thomas C., M. Messinezy, Nigel Westwood, et al.. (2000). A Polycythemia Vera Update: Diagnosis, Pathobiology, and Treatment. Hematology. 2000(1). 51–68. 1 indexed citations

12.

Heppell-Parton, Amanda, Elizabeth Nacheva, Nigel P. Carter, et al.. (1999). Elucidation of the Mechanism of Homozygous Deletion of 3p12∼13 in the U2020 Cell Line Reveals the Unexpected Involvement of Other Chromosomes. Cancer Genetics and Cytogenetics. 111(2). 105–110. 2 indexed citations

13.

Heppell-Parton, Amanda, Elizabeth Nacheva, Nigel P. Carter, & Pamela Rabbitts. (1999). A Combined Approach of Conventional and Molecular Cytogenetics for Detailed Karyotypic Analysis of the Small Cell Lung Carcinoma Cell Line U2020. Cancer Genetics and Cytogenetics. 108(2). 110–119. 11 indexed citations

14.

Gribble, Susan, et al.. (1999). Comparative Analysis of G-Banding, Chromosome Painting, Locus-Specific Fluorescence In Situ Hybridization, and Comparative Genomic Hybridization in Chronic Myeloid Leukemia Blast Crisis. Cancer Genetics and Cytogenetics. 111(1). 7–17. 32 indexed citations

15.

Łastowska, Maria, Elizabeth Nacheva, Ann Curtis, et al.. (1997). Comparative genomic hybridization study of primary neuroblastoma tumors. Genes Chromosomes and Cancer. 18(3). 162–169. 2 indexed citations

16.

Łastowska, Maria, Elizabeth Nacheva, Ann Curtis, et al.. (1997). Comparative genomic hybridization study of primary neuroblastoma tumors. Genes Chromosomes and Cancer. 18(3). 162–169. 65 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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