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  • 1
    Online Resource
    Online Resource
    Wiley ; 2022
    In:  Clinical and Translational Medicine Vol. 12, No. 12 ( 2022-12)
    In: Clinical and Translational Medicine, Wiley, Vol. 12, No. 12 ( 2022-12)
    Type of Medium: Online Resource
    ISSN: 2001-1326 , 2001-1326
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2022
    detail.hit.zdb_id: 2697013-2
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  • 2
    Online Resource
    Online Resource
    Wiley ; 2010
    In:  Proteins: Structure, Function, and Bioinformatics Vol. 78, No. 2 ( 2010-02-01), p. 309-324
    In: Proteins: Structure, Function, and Bioinformatics, Wiley, Vol. 78, No. 2 ( 2010-02-01), p. 309-324
    Type of Medium: Online Resource
    ISSN: 0887-3585 , 1097-0134
    URL: Issue
    RVK:
    Language: English
    Publisher: Wiley
    Publication Date: 2010
    detail.hit.zdb_id: 1475032-6
    SSG: 12
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  • 3
    In: Journal of Child Psychology and Psychiatry, Wiley, Vol. 52, No. 4 ( 2011-04), p. 504-516
    Abstract: The study of the developing brain has begun to shed light on the underpinnings of both early and adult onset neuropsychiatric disorders. Neuroimaging of the human brain across developmental time points and the use of model animal systems have combined to reveal brain systems and gene products that may play a role in autism spectrum disorders, attention deficit hyperactivity disorder, obsessive compulsive disorder and many other neurodevelopmental conditions. However, precisely how genes may function in human brain development and how they interact with each other leading to psychiatric disorders is unknown. Because of an increasing understanding of neural stem cells and how the nervous system subsequently develops from these cells, we have now the ability to study disorders of the nervous system in a new way – by rewinding and reviewing the development of human neural cells. Induced pluripotent stem cells (iPSCs), developed from mature somatic cells, have allowed the development of specific cells in patients to be observed in real time. Moreover, they have allowed some neuronal‐specific abnormalities to be corrected with pharmacological intervention in tissue culture. These exciting advances based on the use of iPSCs hold great promise for understanding, diagnosing and, possibly, treating psychiatric disorders. Specifically, examination of iPSCs from typically developing individuals will reveal how basic cellular processes and genetic differences contribute to individually unique nervous systems. Moreover, by comparing iPSCs from typically developing individuals and patients, differences at stem cell stages, through neural differentiation, and into the development of functional neurons may be identified that will reveal opportunities for intervention. The application of such techniques to early onset neuropsychiatric disorders is still on the horizon but has become a reality of current research efforts as a consequence of the revelations of many years of basic developmental neurobiological science.
    Type of Medium: Online Resource
    ISSN: 0021-9630 , 1469-7610
    URL: Issue
    RVK:
    Language: English
    Publisher: Wiley
    Publication Date: 2011
    detail.hit.zdb_id: 1470297-6
    SSG: 5,2
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  • 4
    In: Protein Science, Wiley, Vol. 20, No. 10 ( 2011-10), p. 1745-1754
    Abstract: The integration of molecular networks with other types of data, such as changing levels of gene expression or protein‐structural features, can provide richer information about interactions than the simple node‐and‐edge representations commonly used in the network community. For example, the mapping of 3D‐structural data onto networks enables classification of proteins into singlish‐ or multi‐interface hubs (depending on whether they have 〉 2 interfaces). Similarly, interactions can be classified as permanent or transient, depending on whether their interface is used by only one or by multiple partners. Here, we incorporate an additional dimension into molecular networks: dynamic conformational changes. We parse the entire PDB structural databank for alternate conformations of proteins and map these onto the protein interaction network, to compile a first version of the Dynamic Structural Interaction Network (DynaSIN). We make this network available as a readily downloadable resource file, and we then use it to address a variety of downstream questions. In particular, we show that multi‐interface hubs display a greater degree of conformational change than do singlish‐interface ones; thus, they show more plasticity which perhaps enables them to utilize more interfaces for interactions. We also find that transient associations involve smaller conformational changes than permanent ones. Although this may appear counterintuitive, it is understandable in the following framework: as proteins involved in transient interactions shuttle between interchangeable associations, they interact with domains that are similar to each other and so do not require drastic structural changes for their activity. We provide evidence for this hypothesis through showing that interfaces involved in transient interactions bind fewer classes of domains than those in a control set.
    Type of Medium: Online Resource
    ISSN: 0961-8368 , 1469-896X
    URL: Issue
    RVK:
    Language: English
    Publisher: Wiley
    Publication Date: 2011
    detail.hit.zdb_id: 2000025-X
    SSG: 12
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  • 5
    In: Cancer Medicine, Wiley, Vol. 5, No. 4 ( 2016-04), p. 631-639
    Abstract: Paclitaxel‐induced peripheral neuropathy ( PIPN ) cannot be predicted from clinical parameters and might have a pharmacogenomic basis. Previous studies identified single nucleotide variants ( SNV ) associated with PIPN . However, only a subset of findings has been confirmed to date in more than one study, suggesting a need for further re‐testing and validation in additional clinical cohorts. Candidate PIPN ‐associated SNVs were identified from the literature. SNVs were retested in 119 patients selected by extreme phenotyping from 269 in NCCTG N08C1 (Alliance) as previously reported. SNV genotyping was performed by a combination of short‐read sequencing analysis and Taqman PCR . These 22 candidate PIPN SNVs were genotyped. Two of these, rs7349683 in the EPHA 5 and rs3213619 in ABCB 1 were found to be significantly associated with PIPN with an Odds ratios OR  = 2.07 ( P  = 0.02) and OR  = 0.12 ( P  = 0.03), respectively. In addition, three SNVs showed a trend toward a risk‐ or protective effect that was consistent with previous reports. The rs10509681 and rs11572080 in the gene CYP 2C8*3 showed risk effect with an OR  = 1.49 and rs1056836 in CYP 1B1 showed a protective effect with an OR  = 0.66. None of the other results supported the previously reported associations, including some SNVs displaying an opposite direction of effect from previous reports, including rs1058930 in CYP 2C8, rs17222723 and rs8187710 in ABCC 2 , rs10771973 in FGD 4 , rs16916932 in CACNB 2 and rs16948748 in PITPNA . Alliance N08C1 validated or supported a minority of previously reported SNV ‐ PIPN associations. Associations previously reported by multiple studies appeared to have a higher likelihood to be validated by Alliance N08C1.
    Type of Medium: Online Resource
    ISSN: 2045-7634 , 2045-7634
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2016
    detail.hit.zdb_id: 2659751-2
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  • 6
    In: Child Development, Wiley, Vol. 84, No. 1 ( 2013-01), p. 34-48
    Type of Medium: Online Resource
    ISSN: 0009-3920
    RVK:
    Language: English
    Publisher: Wiley
    Publication Date: 2013
    detail.hit.zdb_id: 215602-7
    detail.hit.zdb_id: 2047406-4
    SSG: 5,2
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  • 7
    Online Resource
    Online Resource
    Wiley ; 2004
    In:  Protein Science Vol. 13, No. 7 ( 2004-07), p. 1865-1874
    In: Protein Science, Wiley, Vol. 13, No. 7 ( 2004-07), p. 1865-1874
    Abstract: Similarity of protein structures has been analyzed using three‐dimensional Delaunay triangulation patterns derived from the backbone representation. It has been found that structurally related proteins have a common spatial invariant part, a set of tetrahedrons, mathematically described as a common spatial subgraph volume of the three‐dimensional contact graph derived from Delaunay tessellation (DT). Based on this property of protein structures, we present a novel common volume superimposition (TOPOFIT) method to produce structural alignments. Structural alignments usually evaluated by a number of equivalent (aligned) positions (N e ) with corresponding root mean square deviation (RMSD). The superimposition of the DT patterns allows one to uniquely identify a maximal common number of equivalent residues in the structural alignment. In other words, TOPOFIT identifies a feature point on the RMSD N e curve, a topomax point, until which the topologies of two structures correspond to each other, including backbone and interresidue contacts, whereas the growing number of mismatches between the DT patterns occurs at larger RMSD (N e ) after the topomax point. It has been found that the topomax point is present in all alignments from different protein structural classes; therefore, the TOPOFIT method identifies common, invariant structural parts between proteins. The alignments produced by the TOPOFIT method have a good correlation with alignments produced by other current methods. This novel method opens new opportunities for the comparative analysis of protein structures and for more detailed studies on understanding the molecular principles of tertiary structure organization and functionality. The TOPOFIT method also helps to detect conformational changes, topological differences in variable parts, which are particularly important for studies of variations in active/ binding sites and protein classification.
    Type of Medium: Online Resource
    ISSN: 0961-8368 , 1469-896X
    RVK:
    Language: English
    Publisher: Wiley
    Publication Date: 2004
    detail.hit.zdb_id: 2000025-X
    SSG: 12
    Location Call Number Limitation Availability
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