Dataset Information

Prediction of P53 mutants (multiple sites) transcriptional activity based on structural (2D&3D) properties.

ABSTRACT: Prediction of secondary site mutations that reinstate mutated p53 to normalcy has been the focus of intense research in the recent past owing to the fact that p53 mutants have been implicated in more than half of all human cancers and restoration of p53 causes tumor regression. However laboratory investigations are more often laborious and resource intensive but computational techniques could well surmount these drawbacks. In view of this, we formulated a novel approach utilizing computational techniques to predict the transcriptional activity of multiple site (one-site to five-site) p53 mutants. The optimal MCC obtained by the proposed approach on prediction of one-site, two-site, three-site, four-site and five-site mutants were 0.775,0.341,0.784,0.916 and 0.655 respectively, the highest reported thus far in literature. We have also demonstrated that 2D and 3D features generate higher prediction accuracy of p53 activity and our findings revealed the optimal results for prediction of p53 status, reported till date. We believe detection of the secondary site mutations that suppress tumor growth may facilitate better understanding of the relationship between p53 structure and function and further knowledge on the molecular mechanisms and biological activity of p53, a targeted source for cancer therapy. We expect that our prediction methods and reported results may provide useful insights on p53 functional mechanisms and generate more avenues for utilizing computational techniques in biological data analysis.

SUBMITTER: Ramani RG

PROVIDER: S-EPMC3572112 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Prediction of P53 mutants (multiple sites) transcriptional activity based on structural (2D&3D) properties.

Ramani R Geetha RG Jacob Shomona Gracia SG

PloS one 20130213 2

Prediction of secondary site mutations that reinstate mutated p53 to normalcy has been the focus of intense research in the recent past owing to the fact that p53 mutants have been implicated in more than half of all human cancers and restoration of p53 causes tumor regression. However laboratory investigations are more often laborious and resource intensive but computational techniques could well surmount these drawbacks. In view of this, we formulated a novel approach utilizing computational t ...[more]

PMID: 23468845

Similar Datasets

Project description:BACKGROUND:Topologically associating domains (TADs) are genomic regions with varying lengths. The interactions within TADs are more frequent than those between different TADs. TADs or sub-TADs are considered the structural and functional units of the mammalian genomes. Although TADs are important for understanding how genomes function, we have limited knowledge about their 3D structural properties. RESULTS:In this study, we designed and benchmarked three metrics for capturing the three-dimensional and two-dimensional structural signatures of TADs, which can help better understand TADs' structural properties and the relationships between structural properties and genetic and epigenetic features. The first metric for capturing 3D structural properties is radius of gyration, which in this study is used to measure the spatial compactness of TADs. The mass value of each DNA bead in a 3D structure is novelly defined as one or more genetic or epigenetic feature(s). The second metric is folding degree. The last metric is exponent parameter, which is used to capture the 2D structural properties based on TADs' Hi-C contact matrices. In general, we observed significant correlations between the three metrics and the genetic and epigenetic features. We made the same observations when using H3K4me3, transcription start sites, and RNA polymerase II to represent the mass value in the modified radius-of-gyration metric. Moreover, we have found that the TADs in the clusters of depleted chromatin states apparently correspond to smaller exponent parameters and larger radius of gyrations. In addition, a new objective function of multidimensional scaling for modelling chromatin or TADs 3D structures was designed and benchmarked, which can handle the DNA bead-pairs with zero Hi-C contact values. CONCLUSIONS:The web server for reconstructing chromatin 3D structures using multiple different objective functions and the related source code are publicly available at http://dna.cs.miami.edu/3DChrom/.

Project description:Predicting motion is essential for many everyday life activities, e.g., in road traffic. Previous studies on motion prediction failed to find consistent results, which might be due to the use of very different stimulus material and behavioural tasks. Here, we directly tested the influence of task (detection, extrapolation) and stimulus features (visual vs. audiovisual and three-dimensional vs. non-three-dimensional) on temporal motion prediction in two psychophysical experiments. In both experiments a ball followed a trajectory toward the observer and temporarily disappeared behind an occluder. In audiovisual conditions a moving white noise (congruent or non-congruent to visual motion direction) was presented concurrently. In experiment 1 the ball reappeared on a predictable or a non-predictable trajectory and participants detected when the ball reappeared. In experiment 2 the ball did not reappear after occlusion and participants judged when the ball would reach a specified position at two possible distances from the occluder (extrapolation task). Both experiments were conducted in three-dimensional space (using stereoscopic screen and polarised glasses) and also without stereoscopic presentation. Participants benefitted from visually predictable trajectories and concurrent sounds during detection. Additionally, visual facilitation was more pronounced for non-3D stimulation during detection task. In contrast, for a more complex extrapolation task group mean results indicated that auditory information impaired motion prediction. However, a post hoc cross-validation procedure (split-half) revealed that participants varied in their ability to use sounds during motion extrapolation. Most participants selectively profited from either near or far extrapolation distances but were impaired for the other one. We propose that interindividual differences in extrapolation efficiency might be the mechanism governing this effect. Together, our results indicate that both a realistic experimental environment and subject-specific differences modulate the ability of audiovisual motion prediction and need to be considered in future research.

Project description:To provide a comprehensive assessment of patient setup accuracy in 6 degrees of freedom (DOFs) using 2-dimensional/3-dimensional (2D/3D) image registration with on-board 2-dimensional kilovoltage (OB-2 DkV) radiographic images, we evaluated cranial, head and neck (HN), and thoracic and abdominal sites under clinical conditions. A fast 2D/3D image registration method using graphics processing unit GPU was modified for registration between OB-2 DkV and 3D simulation computed tomography (simCT) images, with 3D/3D registration as the gold standard for 6 DOF alignment. In 2D/3D registration, body roll rotation was obtained solely by matching orthogonal OB-2 DkV images with a series of digitally reconstructed radiographs (DRRs) from simCT with a small rotational increment along the gantry rotation axis. The window/level adjustments for optimal visualization of the bone in OB-2 DkV and DRRs were performed prior to registration. Ideal patient alignment at the isocenter was calculated and used as an initial registration position. In 3D/3D registration, cone-beam CT (CBCT) was aligned to simCT on bony structures using a bone density filter in 6DOF. Included in this retrospective study were 37 patients treated in 55 fractions with frameless stereotactic radiosurgery or stereotactic body radiotherapy for cranial and paraspinal cancer. A cranial phantom was used to serve as a control. In all cases, CBCT images were acquired for patient setup with subsequent OB-2 DkV verification. It was found that the accuracy of the 2D/3D registration was 0.0 ± 0.5 mm and 0.1° ± 0.4° in phantom. In patient, it is site dependent due to deformation of the anatomy: 0.2 ± 1.6 mm and -0.4° ± 1.2° on average for each dimension for the cranial site, 0.7 ± 1.6 mm and 0.3° ± 1.3° for HN, 0.7 ± 2.0 mm and -0.7° ± 1.1° for the thorax, and 1.1 ± 2.6 mm and -0.5° ± 1.9° for the abdomen. Anatomical deformation and presence of soft tissue in 2D/3D registration affect the consistency with 3D/3D registration in 6 DOF: the discrepancy increases in superior to inferior direction.

Dataset Information

Prediction of P53 mutants (multiple sites) transcriptional activity based on structural (2D&3D) properties.

Publications

Prediction of P53 mutants (multiple sites) transcriptional activity based on structural (2D&3D) properties.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure