| 1. |
- Linde, Jörg, et al.
(författare)
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Network Properties for Ranking Predicted miRNA Targets in Breast Cancer
- 2009
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Ingår i: Advances in Bioinformatics. - : Hindawi Publishing Corporation. - 1687-8027 .- 1687-8035. ; , s. Article ID 182689-
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Tidskriftsartikel (refereegranskat)abstract
- MicroRNAs control the expression of their target genes by translational repression and transcriptional cleavage. They are involved in various biological processes including development and progression of cancer. To uncover the biological role of miRNAs it is important to identify their target genes. The small number of experimentally validated target genes makes computer prediction methods very important. However, state-of-the-art prediction tools result in a great number of putative targets with an unpredictable number of false positives. In this paper, we propose and evaluate two approaches for ranking the biological relevance of putative targets of miRNAs which are associated with breast cancer.
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| 2. |
- Nilsson, Christer, et al.
(författare)
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Characterization of therapy-related acute myeloid leukemia : increasing incidence and prognostic implications
- 2023
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Ingår i: Haematologica. - : Ferrata Storti Foundation. - 0390-6078 .- 1592-8721. ; 108:4, s. 1015-1025
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Tidskriftsartikel (refereegranskat)abstract
- Studies of therapy-related AML (t-AML) are usually performed in selected cohorts and reliable incidence rates are lacking. In this study, we characterized, defined the incidence over time and studied prognostic implications in all t-AML patients diagnosed in Sweden between 1997 and 2015. Data were retrieved from nationwide population-based registries. In total, 6,779 AML patients were included in the study, of whom 686 (10%) had t-AML. The median age for t-AML was 71 years and 392 (57%) patients were females. During the study period, the incidence of t-AML almost doubled with a yearly increase in t-AML of 4.5% (95% confidence interval: 2.8%-6.2%), which contributed significantly to the general increase in AML incidence over the study period. t-AML solidly constituted over 10% of all AML cases during the later period of the study. Primary diagnoses with the largest increase in incidence and decrease in mortality rate during the study period (i.e., breast and prostate cancer) contributed significantly to the increased incidence of t-AML. In multivariable analysis, t-AML was associated with poorer outcome in cytogenetically intermediate-and adverse-risk cases but t-AML had no significant impact on outcome in favorable-risk AML, including core binding leukemias, acute promyelocytic leukemia and AML with mutated NPM1 without FLT3-ITD. We conclude that there is a strong increase in incidence in t-AML over time and that t-AML constitutes a successively larger proportion of the AML cases. Furthermore, we conclude that t-AML confers a poor prognosis in cytogenetically intermediate-and adverse-risk, but not in favorable-risk AML.
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| 3. |
- Schleicher, Jana, et al.
(författare)
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Facing the challenges of multiscale modelling of bacterial and fungal pathogen-host interactions
- 2017
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Ingår i: Briefings in Functional Genomics & Proteomics. - : Oxford University Press. - 2041-2649 .- 2041-2657. ; 16:2, s. 57-69
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Tidskriftsartikel (refereegranskat)abstract
- Recent and rapidly evolving progress on high-throughput measurement techniques and computational performance has led to the emergence of new disciplines, such as systems medicine and translational systems biology. At the core of these disciplines lies the desire to produce multiscale models: mathematical models that integrate multiple scales of biological organization, ranging from molecular, cellular and tissue models to organ, whole-organism and population scale models. Using such models, hypotheses can systematically be tested. In this review, we present state-of-the-art multiscale modelling of bacterial and fungal infections, considering both the pathogen and host as well as their interaction. Multiscale modelling of the interactions of bacteria, especially Mycobacterium tuberculosis, with the human host is quite advanced. In contrast, models for fungal infections are still in their infancy, in particular regarding infections with the most important human pathogenic fungi, Candida albicans and Aspergillus fumigatus. We reflect on the current availability of computational approaches for multiscale modelling of host-pathogen interactions and point out current challenges. Finally, we provide an outlook for future requirements of multiscale modelling.
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