Mining Gene Ontology Data with AGENDA

The Gene Ontology (GO) initiative is a collaborative effort that uses controlled vocabularies for annotating genetic information. We here present AGENDA (Application for mining Gene Ontology Data), a novel web-based tool for accessing the GO database. AGENDA allows the user to simultaneously retrieve and compare gene lists linked to different GO terms in diverse species using batch queries, facilitating comparative approaches to genetic information. The web-based application offers diverse search options and allows the user to bookmark, visualize, and download the results. AGENDA is an open source web-based application that is freely available for non-commercial use at the project homepage. URL: http://sourceforge.net/projects/bioagenda

DNA methylome analysis in Burkitt and follicular lymphomas identifies differentially methylated regions linked to somatic mutation and transcriptional control

Although Burkitt lymphomas and follicular lymphomas both have features of germinal center B cells, they are biologically and clinically quite distinct. Here we performed whole-genome bisulfite, genome and transcriptome sequencing in 13 IG-MYC translocation-positive Burkitt lymphoma, nine BCL2 translocation-positive follicular lymphoma and four normal germinal center B cell samples. Comparison of Burkitt and follicular lymphoma samples showed differential methylation of intragenic regions that strongly correlated with expression of associated genes, for example, genes active in germinal center dark-zone and light-zone B cells. Integrative pathway analyses of regions differentially methylated in Burkitt and follicular lymphomas implicated DNA methylation as cooperating with somatic mutation of sphingosine phosphate signaling, as well as the TCF3-ID3 and SWI/SNF complexes, in a large fraction of Burkitt lymphomas. Taken together, our results demonstrate a tight connection between somatic mutation, DNA methylation and transcriptional control in key B cell pathways deregulated differentially in Burkitt lymphoma and other germinal center B cell lymphomas

An organelle-specific protein landscape identifies novel diseases and molecular mechanisms

Contains fulltext : 158967.pdf (publisher's version ) (Open Access)Cellular organelles provide opportunities to relate biological mechanisms to disease. Here we use affinity proteomics, genetics and cell biology to interrogate cilia: poorly understood organelles, where defects cause genetic diseases. Two hundred and seventeen tagged human ciliary proteins create a final landscape of 1,319 proteins, 4,905 interactions and 52 complexes. Reverse tagging, repetition of purifications and statistical analyses, produce a high-resolution network that reveals organelle-specific interactions and complexes not apparent in larger studies, and links vesicle transport, the cytoskeleton, signalling and ubiquitination to ciliary signalling and proteostasis. We observe sub-complexes in exocyst and intraflagellar transport complexes, which we validate biochemically, and by probing structurally predicted, disruptive, genetic variants from ciliary disease patients. The landscape suggests other genetic diseases could be ciliary including 3M syndrome. We show that 3M genes are involved in ciliogenesis, and that patient fibroblasts lack cilia. Overall, this organelle-specific targeting strategy shows considerable promise for Systems Medicine

Das Virtuelle Ohr: Aufklärung der Funktionsweise des Transducers in Fliegenohr

Die mechano-elektrische Transduktion bildet das Zentrum des Hörprozesses bei Drosophila. Durch vor Kurzem vorgenommene Studien über das Hörsystem von Vertebraten und Invertebraten wurden neue Erkenntnisse über die Funktionsweise der Transduktionsmaschinarie gewonnen. Die meisten Proteine, die diese Maschinarie bilden, sind noch unbekannt und ebenso deren Funktionalitäten. Das Hörorgan von Drosophila melanogaster dient der Hörforschung als häufiges Modelsystem. Ein physikalisch-mathematisches Modell, das die auditorischen Eigenschaften in Drosophila beschreibt, wurde kürzlich veröffentlicht. Dieses Modell beschreibt das Fliegenohr mit zwei gegenüberliegenden Populationen von Transduktionsmodulen, die zu dem Schallempfänger der Fliegenantenne, welcher die Funktion eines harmonischen Oszillators annimmt, gekoppelt sind. Die funktionellen Komponenten dieses Models können verwendet werden, den Einfluss der molekularen Komponenten auf die makroskopischen Eigenschaften zu bewerten. Das virtuelle Fliegenohr, eine in-silico Anwendung des Hörorgans von Drosophila, hat das Ziel eines high-throughput Programms. Es ist einfach anzuwenden, um die auditorischen Eigenschaften in Mutanten als auch in Wildtypen zu analysieren. Es kann auch als Model verwendet werden, welches den Einfluss der Veränderung von Parametern auf molekularer Ebene analysiert. Durch die Verwendung des virtuellen Ohrs versuchen wir die Veränderung der makroskopischen Mechanismen durch Mutationen mit den Veränderungen der Parameter des Fliegenhörorgans auf molekularer Ebene zu verknüpfen. Dies erlaubt die Untersuchung der Verknüpfung von Tranduktionsfunktion und Genen. Neben der Modelierung wird eine neuartige Mothode zur Untersuchung der auditorischen Funktion vorgestellt, die die Quantifizierung des Leistungsflusses im Fliegenohr erlaubt

Mining Gene Ontology Data with AGENDA

The Gene Ontology (GO) initiative is a collaborative effort that uses controlled vocabularies for annotating genetic information. We here present AGENDA (Application for mining Gene Ontology Data), a novel web-based tool for accessing the GO database. AGENDA allows the user to simultaneously retrieve and compare gene lists linked to different GO terms in diverse species using batch queries, facilitating comparative approaches to genetic information. The web-based application offers diverse search options and allows the user to bookmark, visualize, and download the results. AGENDA is an open source web-based application that is freely available for non-commercial use at the project homepage. URL: http://sourceforge.net/projects/bioagenda

Robust Image Matching Based on Image Feature and Depth Information Fusion

In this paper, we propose a robust image feature extraction and fusion method to effectively fuse image feature and depth information and improve the registration accuracy of RGB-D images. The proposed method directly splices the image feature point descriptors with the corresponding point cloud feature descriptors to obtain the fusion descriptor of the feature points. The fusion feature descriptor is constructed based on the SIFT, SURF, and ORB feature descriptors and the PFH and FPFH point cloud feature descriptors. Furthermore, the registration performance based on fusion features is tested through the RGB-D datasets of YCB and KITTI. ORBPFH reduces the false-matching rate by 4.66~16.66%, and ORBFPFH reduces the false-matching rate by 9~20%. The experimental results show that the RGB-D robust feature extraction and fusion method proposed in this paper is suitable for the fusion of ORB with PFH and FPFH, which can improve feature representation and registration, representing a novel approach for RGB-D image matching

Physics-Based TOF Imaging Simulation for Space Targets Based on Improved Path Tracing

Aiming at the application of close-up space measurement based on time-of-flight (TOF) cameras, according to the analysis of the characteristics of the space background environment and the imaging characteristics of the TOF camera, a physics-based amplitude modulated continuous wave (AMCW) TOF camera imaging simulation method for space targets based on the improved path tracing is proposed. Firstly, the microfacet bidirectional reflection distribution function (BRDF) model of several typical space target surface materials is fitted according to the measured BRDF data in the TOF camera response band to make it physics-based. Secondly, an improved path tracing algorithm is developed to adapt to the TOF camera by introducing a cosine component to characterize the modulated light in the TOF camera. Then, the imaging link simulation model considering the coupling effects of the BRDF of materials, the suppression of background illumination (SBI), optical system, detector, electronic equipment, platform vibration, and noise is established, and the simulation images of the TOF camera are obtained. Finally, ground tests are carried out, and the test shows that the relative error of the grey mean, grey variance, depth mean, and depth variance is 2.59%, 3.80%, 18.29%, and 14.58%, respectively; the MSE, SSIM, and PSNR results of our method are also better than those of the reference method. The ground test results verify the correctness of the proposed simulation model, which can provide image data support for the ground test of TOF camera algorithms for space targets

Space-Based THz Radar Fly-Around Imaging Simulation for Space Targets Based on Improved Path Tracing

Aiming at the space target detection application of a space-based terahertz (THz) radar, according to the imaging mechanism of broadband THz radars, a THz radar imaging simulation method based on improved path tracing is proposed. Firstly, the characterization method of THz scattering characteristics based on Kirchhoff’s approximation method is introduced. The multi-parameter THz bidirectional reflectance distribution function (THz-BRDF) models of aluminum (Al), white-painted Al, and polyimide film at 0.215 THz are fitted according to the theoretical data, with fitting errors below 4%. Then, the THz radar imaging simulation method based on improved path tracing is presented in detail. The simulation method utilizes path tracing to simulate parallelized THz radar echo signal data, considering multi-path energy scattering based on the THz-BRDF model. Finally, we conducted THz radar imaging simulation experiments. The influences in the imaging process of different fly-around motions are analyzed, and a comparison experiment is conducted with the fast-physical optics (FPO) method. The comparative results indicate that the proposed method exhibits richer and more realistic features compared with the FPO method. The simulation experiments results demonstrate that the proposed method can provide a data source for ground algorithm testing of THz radars, particularly in evaluating the target detection and recognition algorithm based on deep learning, providing strong support for the application of space-based THz radars in the future

Binary Feature Description of 3D Point Cloud Based on Retina-like Sampling on Projection Planes

A binary feature description and registration algorithm for a 3D point cloud based on retina-like sampling on projection planes (RSPP) are proposed in this paper. The algorithm first projects the point cloud within the support radius around the key point to the XY, YZ, and XZ planes of the Local Reference Frame (LRF) and performs retina-like sampling on the projection plane. Then, the binarized Gaussian density weight values at the sampling points are calculated and encoded to obtain the RSPP descriptor. Finally, rough registration of point clouds is performed based on the RSPP descriptor, and the RANSAC algorithm is used to optimize the registration results. The performance of the proposed algorithm is tested on public point cloud datasets. The test results show that the RSPP-based point cloud registration algorithm has a good registration effect under no noise, 0.25 mr, and 0.5 mr Gaussian noise. The experimental results verify the correctness and robustness of the proposed registration method, which can provide theoretical and technical support for the 3D point cloud registration application