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Oliver Hofmann

Researcher at University of Melbourne

Publications -  113
Citations -  18736

Oliver Hofmann is an academic researcher from University of Melbourne. The author has contributed to research in topics: Genome & Gene. The author has an hindex of 38, co-authored 104 publications receiving 15366 citations. Previous affiliations of Oliver Hofmann include University of Bergen & University of Cologne.

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A comprehensive promoter landscape identifies a novel promoter for CD133 in restricted tissues, cancers, and stem cells

TL;DR: A novel proximal promoter (P6) is identified within CD133+ melanoma cell lines and stem cells and is enriched with respect to previously characterized PROM1 promoters for a HMGI/Y (HMGA1) family transcription factor binding site motif and exhibits different epigenetic modifications relative to the canonical promoter region ofPROM1.
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A two-state analysis of co-operative oxygen binding in the three human embryonic haemoglobins.

TL;DR: Fast-reaction studies have been used to determine the rate constants of the oxygen association and dissociation processes occurring in the R-state and the rate of the allosteric R > T conformational transition and suggest a likely reason for the high affinity and low co-operativity of the embryonic proteins.
Posted ContentDOI

Cancer Predisposition Sequencing Reporter (CPSR): a flexible variant report engine for germline screening in cancer

TL;DR: The Cancer Predisposition Sequencing Reporter (CPSR), an open-source computational workflow that generates a structured report of germline variants identified in known cancer predisposition genes, highlighting markers of therapeutic, prognostic, and diagnostic relevance, demonstrates superior sensitivity and comparable specificity for the detection of pathogenic variants when compared to existing algorithms.
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Deep targeted sequencing of 12 breast cancer susceptibility regions in 4611 women across four different ethnicities

TL;DR: This study illustrates some of the challenges faced in fine-mapping studies in the post-GWAS era, most importantly the large sample sizes needed to identify rare-variant associations or to distinguish the effects of strongly correlated common SNVs.
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Prioritizing genes of potential relevance to diseases affected by sex hormones: an example of Myasthenia Gravis

TL;DR: The ab-initio approach outperforms the other methods for prioritizing disease-associated genes under the potential control of sex hormones and has a potential to be adapted to prioritize genes relevant to other diseases.