Janet L. Lukacs

845 total citations
27 papers, 680 citations indexed

About

Janet L. Lukacs is a scholar working on Molecular Biology, Hematology and Genetics. According to data from OpenAlex, Janet L. Lukacs has authored 27 papers receiving a total of 680 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 14 papers in Hematology and 9 papers in Genetics. Recurrent topics in Janet L. Lukacs's work include Multiple Myeloma Research and Treatments (14 papers), Genomic variations and chromosomal abnormalities (9 papers) and Glycosylation and Glycoproteins Research (7 papers). Janet L. Lukacs is often cited by papers focused on Multiple Myeloma Research and Treatments (14 papers), Genomic variations and chromosomal abnormalities (9 papers) and Glycosylation and Glycoproteins Research (7 papers). Janet L. Lukacs collaborates with scholars based in United States. Janet L. Lukacs's co-authors include Jeffrey R. Sawyer, Bart Barlogie, John D. Shaughnessy, Nikhil C. Munshi, David S. Siegel, K.R. Desikan, Seema Singhal, Jayesh Mehta, Charles M. Swanson and Erming Tian and has published in prestigious journals such as Blood, Cancer and British Journal of Haematology.

In The Last Decade

Janet L. Lukacs

24 papers receiving 668 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Janet L. Lukacs United States	12	386	383	145	133	109	27	680
Sverre Heim Sweden	14	278 0.7×	200 0.5×	143 1.0×	94 0.7×	65 0.6×	16	706
Stéphanie Struski France	16	264 0.7×	171 0.4×	106 0.7×	112 0.8×	134 1.2×	30	596
Jacqueline R. Batanian United States	15	206 0.5×	113 0.3×	186 1.3×	82 0.6×	82 0.8×	56	568
Rizwan Naeem United States	15	194 0.5×	142 0.4×	110 0.8×	164 1.2×	71 0.7×	31	700
Nicola Foot United Kingdom	14	402 1.0×	481 1.3×	120 0.8×	200 1.5×	213 2.0×	25	837
J L Laï France	13	372 1.0×	797 2.1×	79 0.5×	146 1.1×	270 2.5×	23	942
Javier Suela Spain	13	268 0.7×	158 0.4×	145 1.0×	61 0.5×	83 0.8×	31	539
Marie‐Josée Le Bris France	18	420 1.1×	551 1.4×	220 1.5×	75 0.6×	235 2.2×	55	986
JR Downing United States	9	331 0.9×	534 1.4×	56 0.4×	83 0.6×	78 0.7×	9	823
Christoph E. Heilig Germany	11	265 0.7×	136 0.4×	60 0.4×	135 1.0×	53 0.5×	32	547

Countries citing papers authored by Janet L. Lukacs

Since Specialization

Citations

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

Fields of papers citing papers by Janet L. Lukacs

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Janet L. Lukacs. 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 Janet L. Lukacs. The network helps show where Janet L. Lukacs may publish in the future.

Co-authorship network of co-authors of Janet L. Lukacs

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

All Works

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20 of 20 papers shown

Sawyer, Jeffrey R., Erming Tian, Brian A. Walker, et al.. (2019). An acquired high-risk chromosome instability phenotype in multiple myeloma: Jumping 1q Syndrome. Blood Cancer Journal. 9(8). 62–62. 30 indexed citations

Sawyer, Jeffery R., Erming Tian, Brian A. Walker, et al.. (2018). An Acquired High-Risk Chromosome Instability Phenotype in Multiple Myeloma: Jumping 1q Syndrome. Blood. 132(Supplement 1). 4489–4489. 5 indexed citations

Sawyer, Jeffrey R., John D. Shaughnessy, Joshua Epstein, et al.. (2016). Hyperhaploidy is a novel high-risk cytogenetic subgroup in multiple myeloma. Leukemia. 31(3). 637–644. 21 indexed citations

Sawyer, Jeffrey R., Erming Tian, Christoph Heuck, et al.. (2015). Evidence of an epigenetic origin for high-risk 1q21 copy number aberrations in multiple myeloma. Blood. 125(24). 3756–3759. 39 indexed citations

Sawyer, Jeffrey R., Erming Tian, Christoph Heuck, et al.. (2012). Hyperhaploid Multiple Myeloma (MM): A Rare Karyotypic Subgroup Retaining Disomy 18 and 1q12∼23 Amplification. Blood. 120(21). 3983–3983. 1 indexed citations

Sawyer, Jeffrey R., Erming Tian, John D. Shaughnessy, et al.. (2011). Jumping Translocations 1q12 Contribute to Copy Number (CN) Alterations in Multiple Myeloma (MM): Unexpected Focal Amplifications of Receptor Chromosomes (RC). Blood. 118(21). 298–298. 1 indexed citations

Sawyer, Jeffrey R., Guido Tricot, Janet L. Lukacs, et al.. (2004). Genomic instability in multiple myeloma: Evidence for jumping segmental duplications of chromosome arm 1q. Genes Chromosomes and Cancer. 42(1). 95–106. 84 indexed citations

Parham, David M., et al.. (2004). Cytogenetic Distinction among Benign Fibro-osseous Lesions of Bone in Children and Adolescents: Value of Karyotypic Findings in Differential Diagnosis. Pediatric and Developmental Pathology. 7(2). 148–158. 26 indexed citations

Sawyer, Jeffrey R., et al.. (2003). Telomeric fusion as a mechanism for the loss of 1p in meningioma. Cancer Genetics and Cytogenetics. 145(1). 38–48. 11 indexed citations

10.

Sawyer, Jeffrey R., Edward L. Thomas, Janet L. Lukacs, et al.. (2002). Recurring breakpoints of 1p13∼p22 in osteochondroma. Cancer Genetics and Cytogenetics. 138(2). 102–106. 9 indexed citations

11.

Sawyer, Jeffrey R., Janet L. Lukacs, Edward L. Thomas, et al.. (2001). Multicolour spectral karyotyping identifies new translocations and a recurring pathway for chromosome loss in multiple myeloma. British Journal of Haematology. 112(1). 167–174. 70 indexed citations

12.

Sawyer, Jeffrey R., Charles M. Swanson, Janet L. Lukacs, et al.. (1998). Evidence of an association between 6q13-21 chromosome aberrations and locally aggressive behavior in patients with cartilage tumors. Cancer. 82(3). 474–483. 56 indexed citations

13.

Sawyer, Jeffrey R., Janet L. Lukacs, Nikhil C. Munshi, et al.. (1998). Identification of New Nonrandom Translocations in Multiple Myeloma With Multicolor Spectral Karyotyping. Blood. 92(11). 4269–4278. 97 indexed citations

14.

Sawyer, Jeffrey R., et al.. (1996). Sub-band deletion of 7q36.3 in a patient with ring chromosome 7: Association with holoprosencephaly. American Journal of Medical Genetics. 65(2). 113–116. 13 indexed citations

15.

Lukacs, Janet L.. (1987). A Product-Line Approach to Nursing Services. The Nurse Practitioner. 12(12). 48???51–48???51. 1 indexed citations

16.

Lukacs, Janet L.. (1984). Strategic Planning in Hospitals. JONA The Journal of Nursing Administration. 14(9). 11???17–11???17. 3 indexed citations

17.

Lukacs, Janet L.. (1984). Cost-Effectiveness of Non-Physician Health Care Professionals. The Nurse Practitioner. 9(10). 54???59–54???59. 10 indexed citations

18.

Lukacs, Janet L.. (1984). Developing a practice definition.. PubMed. 9(4). 59, 62, 70–59, 62, 70.

19.

Lukacs, Janet L.. (1982). Factors in Nurse Practitioner Role Adjustment. The Nurse Practitioner. 7(3). 21???25–21???25. 11 indexed citations

20.

Lukacs, Janet L.. (1972). [Combination technic--treatment attractive to radiotherapy assistants].. PubMed. 39(1). 8–11. 1 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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