What is she best known for?
The fields of study she is best known for:
Anne K. Soutar spends much of her time researching LDL receptor, Endocrinology, Internal medicine, Familial hypercholesterolemia and Apolipoprotein B.
Her LDL receptor research is multidisciplinary, relying on both Mutation and Receptor.
Her In vivo research extends to Endocrinology, which is thematically connected.
Her research in Familial hypercholesterolemia intersects with topics in Genetics and Hyperlipoproteinemia Type II.
Her Genetics study integrates concerns from other disciplines, such as Amyloidosis and Amyloid.
Her Apolipoprotein B research incorporates themes from Hydroxymethylglutaryl-CoA Reductase Inhibitors and Pediatrics.
Her most cited work include:
- Human lysozyme gene mutations cause hereditary systemic amyloidosis (518 citations)
- Mechanisms of Disease: genetic causes of familial hypercholesterolemia (436 citations)
- Defects of receptor-mediated low density lipoprotein catabolism in homozygous familial hypercholesterolemia and hypothyroidism in vivo. (237 citations)
What are the main themes of her work throughout her whole career to date?
Her scientific interests lie mostly in LDL receptor, Internal medicine, Endocrinology, Genetics and Low-density lipoprotein.
Her LDL receptor research includes themes of Receptor and Molecular biology.
Her research on Internal medicine frequently connects to adjacent areas such as Reductase.
Her Endocrinology study often links to related topics such as In vivo.
Her Low-density lipoprotein research includes elements of Catabolism, Very low-density lipoprotein, Low-density lipoprotein receptor-related protein 8 and Northern blot.
Anne K. Soutar has researched Apolipoprotein B in several fields, including Heterozygote advantage and Blood plasma.
She most often published in these fields:
- LDL receptor (44.06%)
- Internal medicine (40.56%)
- Endocrinology (37.76%)
What were the highlights of her more recent work (between 2005-2015)?
- LDL receptor (44.06%)
- PCSK9 (10.49%)
- Internal medicine (40.56%)
In recent papers she was focusing on the following fields of study:
Her main research concerns LDL receptor, PCSK9, Internal medicine, Genetics and Molecular biology.
The study incorporates disciplines such as Exon, Allele and Apolipoprotein B in addition to LDL receptor.
Her biological study spans a wide range of topics, including Mutation, Mutant, Proprotein convertase, Multiplex ligation-dependent probe amplification and Kexin.
Anne K. Soutar combines subjects such as Endocrinology, Surgery and Bioinformatics with her study of Internal medicine.
Her Endocrinology study incorporates themes from Hydroxymethylglutaryl-CoA reductase and Reductase.
Her work focuses on many connections between Genetics and other disciplines, such as Ldlr gene, that overlap with her field of interest in Mutation detection and Functional analysis.
Between 2005 and 2015, her most popular works were:
- Mechanisms of Disease: genetic causes of familial hypercholesterolemia (436 citations)
- Genetic defects causing familial hypercholesterolaemia: identification of deletions and duplications in the LDL-receptor gene and summary of all mutations found in patients attending the Hammersmith Hospital Lipid Clinic. (72 citations)
- Familial hypercholesterolaemia in Portugal (68 citations)
In her most recent research, the most cited papers focused on:
Anne K. Soutar focuses on PCSK9, LDL receptor, Internal medicine, Endocrinology and Mutation.
She combines topics linked to Apolipoprotein B with her work on LDL receptor.
Her Internal medicine study combines topics from a wide range of disciplines, such as Oncology, Bioinformatics and Target enrichment.
Specifically, her work in Endocrinology is concerned with the study of Cholesterol.
Her work carried out in the field of Mutation brings together such families of science as Gene duplication, Lipid metabolism and Multiplex ligation-dependent probe amplification.
Her study looks at the intersection of Familial hypercholesterolemia and topics like Lipoprotein with Exon and Low-density lipoprotein.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
