What is she best known for?
The fields of study she is best known for:
- Gene
- Cancer
- Internal medicine
The scientist’s investigation covers issues in Breast cancer, Genome-wide association study, Genetics, Internal medicine and Estrogen receptor.
Her Breast cancer research includes themes of Cancer research, Single-nucleotide polymorphism, Genotype and Bioinformatics.
Her work carried out in the field of Cancer research brings together such families of science as Methylation, DNA methylation, Pathology, Ductal carcinoma and Epigenetics.
Vessela N. Kristensen has researched Genome-wide association study in several fields, including Mendelian randomization, Disease, Genetic predisposition, Chromatin and Genetic association.
Her studies in Internal medicine integrate themes in fields like Endocrinology, Oncology and Exon.
Her studies deal with areas such as Odds ratio, Epidemiology, Case-control study, Gynecology and Triple-negative breast cancer as well as Oncology.
Her most cited work include:
- Large-scale genotyping identifies 41 new loci associated with breast cancer risk (834 citations)
- Allele-specific copy number analysis of tumors (699 citations)
- MicroRNA related polymorphisms and breast cancer risk (582 citations)
What are the main themes of her work throughout her whole career to date?
Vessela N. Kristensen mainly focuses on Breast cancer, Internal medicine, Oncology, Cancer research and Genetics.
Vessela N. Kristensen interconnects Genome-wide association study, Single-nucleotide polymorphism and Bioinformatics in the investigation of issues within Breast cancer.
Her Genome-wide association study study combines topics in areas such as Expression quantitative trait loci, Case-control study, Endometrial cancer and Disease.
Her Oncology research incorporates themes from Prospective cohort study, Immunology, Ovarian cancer, Gynecology and Colorectal cancer.
Her research in Cancer research intersects with topics in Methylation, DNA methylation, microRNA, Regulation of gene expression and Epigenetics.
Her Cancer study incorporates themes from Mutation and Pathology.
She most often published in these fields:
- Breast cancer (135.36%)
- Internal medicine (60.67%)
- Oncology (54.39%)
What were the highlights of her more recent work (between 2018-2021)?
- Breast cancer (135.36%)
- Cancer research (52.93%)
- Internal medicine (60.67%)
In recent papers she was focusing on the following fields of study:
Her primary scientific interests are in Breast cancer, Cancer research, Internal medicine, Oncology and Gene.
Her Breast cancer study is concerned with the larger field of Cancer.
Her work on Cancer prognosis as part of general Cancer study is frequently linked to Akt/PKB signaling pathway, therefore connecting diverse disciplines of science.
The concepts of her Cancer research study are interwoven with issues in Cancer cell, Immune system, microRNA and Cytokine.
Her Oncology research is multidisciplinary, incorporating perspectives in Odds ratio, Proportional hazards model, Clinical trial and Prostate cancer.
Her Gene study integrates concerns from other disciplines, such as Computational biology and Disease.
Between 2018 and 2021, her most popular works were:
- Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes (257 citations)
- Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes (257 citations)
- Breast cancer quantitative proteome and proteogenomic landscape (52 citations)
In her most recent research, the most cited papers focused on:
Vessela N. Kristensen mainly investigates Breast cancer, Internal medicine, Oncology, Computational biology and Gene.
Her Breast cancer research integrates issues from Cancer research, microRNA, Metastasis and Genome-wide association study.
Vessela N. Kristensen combines subjects such as CHEK2 and PALB2 with her study of Internal medicine.
Her biological study spans a wide range of topics, including Clinical trial, Treatment outcome, Randomized controlled trial, Genetic counseling and Genetic testing.
Her work carried out in the field of Computational biology brings together such families of science as Gene expression profiling, Transcription factor, Expression quantitative trait loci, Genetic association and In silico.
Her studies in Estrogen receptor integrate themes in fields like Bioinformatics, Germline, Medical genetics, Disease and Gene regulatory network.
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