Multi-omics data is frequently measured to enrich the comprehension of biological mechanisms underlying certain phenotypes. However, due to the complex relations and high dimension of multi-omics data, it is difficult to associate omics features to certain biological traits of interest. For example, the clinically valuable breast cancer subtypes are well-defined at the molecular level, but are poorly classified using gene expression data. Here, we propose a multi-omics analysis method called MONTI (Multi-Omics Non-negative Tensor decomposition for Integrative analysis), which goal is to select multi-omics features that are able to represent trait specific characteristics. Here, we demonstrate the strength of multi-omics integrated analysis in terms of cancer subtyping. The multi-omics data are first integrated in a biologically meaningful manner to form a three dimensional tensor, which is then decomposed using a non-negative tensor decomposition method. From the result, MONTI selects highly informative subtype specific multi-omics features. MONTI was applied to three case studies of 597 breast cancer, 314 colon cancer, and 305 stomach cancer cohorts. For all the case studies, we found that the subtype classification accuracy significantly improved when utilizing all available multi-omics data. MONTI was able to detect subtype specific gene sets that showed to be strongly regulated by certain omics, from which correlation between omics types could be inferred. Furthermore, various clinical attributes of nine cancer types were analyzed using MONTI, which showed that some clinical attributes could be well explained using multi-omics data. We demonstrated that integrating multi-omics data in a gene centric manner improves detecting cancer subtype specific features and other clinical features, which may be used to further understand the molecular characteristics of interest. The software and data used in this study are available at: https://github.com/inukj/MONTI.

Structural and functional brain connectivity are increasingly used to identify and analyze group differences in studies of brain disease. This study presents methods to analyze uni- and bi-modal brain connectivity and evaluate their ability to identify differences. Novel visualizations of significantly different connections comparing multiple metrics are presented. On the global level, “bi-modal comparison plots” show the distribution of uni- and bi-modal group differences and the relationship between structure and function. Differences between brain lobes are visualized using “worm plots”. Group differences in connections are examined with an existing visualization, the “connectogram”. These visualizations were evaluated in two proof-of-concept studies: (1) middle-aged versus elderly subjects; and (2) patients with schizophrenia versus controls. Each included two measures derived from diffusion weighted images and two from functional magnetic resonance images. The structural measures w...

Introduction: Anoikis is a form of programmed cell death. Anoikis resistance in hepatocellular carcinoma (HCC) promotes cancer cells shedding from the primary tumor site, thus contributing to survival and distant metastasis. However, the prognostic significance of anoikis-related genes (ARGs) and the biological functions of crucial genes in HCC have not been reported. Objectives: This study aimed to construct a model for predicting the outcome of patients with HCC based on ARGs and to investigate the clinicopathological significance and function of Rac family small GTPase 3 (RAC3) in HCC.

Cisplatin-based chemotherapy is the standard care regimen in bladder cancer (BC). However, resistance to the therapy whose molecular mechanisms of the resistance are not fully elucidated rapidly develops in BC patients. Here we introduced multidimensional proteomic analysis providing different levels of protein information, which included global proteome and phosphorpoteome perturbed by EGF using the cisplatin resistant BC model. Integrated analysis of protein expression and phosphorylation provided comprehensive profiles of altered proteins in cisplatin resistant cells that are dependent and independent on EGF, as well as suggesting significance of protein phosphorylation in resistance mechanisms in BC. From the reconstruction of cisplatin resistance associated network model and subsequent kinase enrichment analysis, we have identified three key kinases, CDK2, CHEK1, and ERBB2 as central regulators mediating cisplatin resistance. Experimental validation showed phosphorylation events in these central kinases and their putative substrates, suggesting evidence that activation of three kinases are important to acquired resistance to cisplatin in BC. Expanded analysis with this proteomic discovery to transcriptome profiles from BC cohorts nominated the 7 gene panel associated with poor survival after cisplatin-based chemotherapy. These findings provide insightful strategies to classify high-risk BC patients upon current chemotherapies and to identify therapeutic targets for recurrence disease.

As an example shown in this study (http:/​/​dx.​doi.​org/​10.​1104/​pp.​113.​233932), we performed a phenotyping experiment on 33 Fernandez maize (Zea mays) plants. This energy maize cultivar was cultivated by the KWS Company. Plant images were captured using a LemnaTec 3D Scanalyzer (LemnaTec, GmbH, Wuerselen, Germany) at the Leibniz Institute of Plant Genetics and Crop Plant Research (IPK Gatersleben, Germany). Seventy-eight images were taken of every plant, of which 26 images were captured using three kinds of cameras. For each camera system, images were taken from both top view (one image) and side view (25 images). The result images were stored in PNG format (this is the JPEG compressed version of this data set). The three cameras used in the automated system are: (i) visible-light camera (Basler Pilot piA2400-17gc with resolution of 2454 x 2056 px), (ii) fluorescence camera (Basler Scout scA1400-17gc with resolution of 1390 x 1038 px) and (iii) near-infrared camera (Nir 300 with resolution of 320 x 256 px). Images were acquired daily for nine weeks. We obtained ~34000 images in total.

Additional file 6. SL_B vs H_B_circRNA_differential_expression

As an example shown in this study (http:/​/​dx.​doi.​org/​10.​1104/​pp.​113.​233932), we performed a phenotyping experiment on 33 Fernandez maize (Zea mays) plants. This energy maize cultivar was cultivated by the KWS Company. Plant images were captured using a LemnaTec 3D Scanalyzer (LemnaTec, GmbH, Wuerselen, Germany) at the Leibniz Institute of Plant Genetics and Crop Plant Research (IPK Gatersleben, Germany). Seventy-eight images were taken of every plant, of which 26 images were captured using three kinds of cameras. For each camera system, images were taken from both top view (one image) and side view (25 images). The result images were stored in PNG format (this is the JPEG compressed version of this data set). The three cameras used in the automated system are: (i) visible-light camera (Basler Pilot piA2400-17gc with resolution of 2454 x 2056 px), (ii) fluorescence camera (Basler Scout scA1400-17gc with resolution of 1390 x 1038 px) and (iii) near-infrared camera (Nir 300 with resolution of 320 x 256 px). Images were acquired daily for nine weeks. We obtained ~34000 images in total.

ABSTRACT Urban afforestation has important functions, but problems related to its management are equally relevant, analysis of which is needed in order to prevent accidents. However, due to the subjectivity in the assessment, there may be uncertainty as to the seriousness of the risk. In order to address this, the present work evaluates a neuro-fuzzy-based methodology for the integrated analysis of risk indicators. From the knowledge of experts and a database with 107 cases, systems were constructed for the multi-criteria analysis of 18 parameters integrated using 3 indexes and 5 indicators. As a result, the model presented accuracies of 95.5% in generalization tests, and almost perfect agreement (kappa > 0.8) with the assessment by the expert. In conclusion, the findings show that this neuro-fuzzy modeling approach represents a promising alternative for supporting risk analysis in urban afforestation.

As an example shown in this study (http:/​/​dx.​doi.​org/​10.​1104/​pp.​113.​233932), we performed a phenotyping experiment on 33 Fernandez maize (Zea mays) plants. This energy maize cultivar was cultivated by the KWS Company. Plant images were captured using a LemnaTec 3D Scanalyzer (LemnaTec, GmbH, Wuerselen, Germany) at the Leibniz Institute of Plant Genetics and Crop Plant Research (IPK Gatersleben, Germany). Seventy-eight images were taken of every plant, of which 26 images were captured using three kinds of cameras. For each camera system, images were taken from both top view (one image) and side view (25 images). The result images were stored in PNG format (this is the JPEG compressed version of this data set). The three cameras used in the automated system are: (i) visible-light camera (Basler Pilot piA2400-17gc with resolution of 2454 x 2056 px), (ii) fluorescence camera (Basler Scout scA1400-17gc with resolution of 1390 x 1038 px) and (iii) near-infrared camera (Nir 300 with resolution of 320 x 256 px). Images were acquired daily for nine weeks. We obtained ~34000 images in total.

As an example shown in this study (http:/​/​dx.​doi.​org/​10.​1104/​pp.​113.​233932), we performed a phenotyping experiment on 33 Fernandez maize (Zea mays) plants. This energy maize cultivar was cultivated by the KWS Company. Plant images were captured using a LemnaTec 3D Scanalyzer (LemnaTec, GmbH, Wuerselen, Germany) at the Leibniz Institute of Plant Genetics and Crop Plant Research (IPK Gatersleben, Germany). Seventy-eight images were taken of every plant, of which 26 images were captured using three kinds of cameras. For each camera system, images were taken from both top view (one image) and side view (25 images). The result images were stored in PNG format (this is the JPEG compressed version of this data set). The three cameras used in the automated system are: (i) visible-light camera (Basler Pilot piA2400-17gc with resolution of 2454 x 2056 px), (ii) fluorescence camera (Basler Scout scA1400-17gc with resolution of 1390 x 1038 px) and (iii) near-infrared camera (Nir 300 with resolution of 320 x 256 px). Images were acquired daily for nine weeks. We obtained ~34000 images in total.

As an example shown in this study (http:/​/​dx.​doi.​org/​10.​1104/​pp.​113.​233932), we performed a phenotyping experiment on 33 Fernandez maize (Zea mays) plants. This energy maize cultivar was cultivated by the KWS Company. Plant images were captured using a LemnaTec 3D Scanalyzer (LemnaTec, GmbH, Wuerselen, Germany) at the Leibniz Institute of Plant Genetics and Crop Plant Research (IPK Gatersleben, Germany). Seventy-eight images were taken of every plant, of which 26 images were captured using three kinds of cameras. For each camera system, images were taken from both top view (one image) and side view (25 images). The result images were stored in PNG format (this is the JPEG compressed version of this data set). The three cameras used in the automated system are: (i) visible-light camera (Basler Pilot piA2400-17gc with resolution of 2454 x 2056 px), (ii) fluorescence camera (Basler Scout scA1400-17gc with resolution of 1390 x 1038 px) and (iii) near-infrared camera (Nir 300 with resolution of 320 x 256 px). Images were acquired daily for nine weeks. We obtained ~34000 images in total.

As an example shown in this study (http:/​/​dx.​doi.​org/​10.​1104/​pp.​113.​233932), we performed a phenotyping experiment on 33 Fernandez maize (Zea mays) plants. This energy maize cultivar was cultivated by the KWS Company. Plant images were captured using a LemnaTec 3D Scanalyzer (LemnaTec, GmbH, Wuerselen, Germany) at the Leibniz Institute of Plant Genetics and Crop Plant Research (IPK Gatersleben, Germany). Seventy-eight images were taken of every plant, of which 26 images were captured using three kinds of cameras. For each camera system, images were taken from both top view (one image) and side view (25 images). The result images were stored in PNG format (this is the JPEG compressed version of this data set). The three cameras used in the automated system are: (i) visible-light camera (Basler Pilot piA2400-17gc with resolution of 2454 x 2056 px), (ii) fluorescence camera (Basler Scout scA1400-17gc with resolution of 1390 x 1038 px) and (iii) near-infrared camera (Nir 300 with resolution of 320 x 256 px). Images were acquired daily for nine weeks. We obtained ~34000 images in total.

As an example shown in this study (http:/​/​dx.​doi.​org/​10.​1104/​pp.​113.​233932), we performed a phenotyping experiment on 33 Fernandez maize (Zea mays) plants. This energy maize cultivar was cultivated by the KWS Company. Plant images were captured using a LemnaTec 3D Scanalyzer (LemnaTec, GmbH, Wuerselen, Germany) at the Leibniz Institute of Plant Genetics and Crop Plant Research (IPK Gatersleben, Germany). Seventy-eight images were taken of every plant, of which 26 images were captured using three kinds of cameras. For each camera system, images were taken from both top view (one image) and side view (25 images). The result images were stored in PNG format (this is the JPEG compressed version of this data set). The three cameras used in the automated system are: (i) visible-light camera (Basler Pilot piA2400-17gc with resolution of 2454 x 2056 px), (ii) fluorescence camera (Basler Scout scA1400-17gc with resolution of 1390 x 1038 px) and (iii) near-infrared camera (Nir 300 with resolution of 320 x 256 px). Images were acquired daily for nine weeks. We obtained ~34000 images in total.

Omics data integration is becoming necessary to investigate the genomic mechanisms involved in complex diseases. During the integration process, many challenges arise such as data heterogeneity, the smaller number of individuals in comparison to the number of parameters, multicollinearity, and interpretation and validation of results due to their complexity and lack of knowledge about biological processes. To overcome some of these issues, innovative statistical approaches are being developed. In this work, we propose a permutation-based method to concomitantly assess significance and correct by multiple testing with the MaxT algorithm. This was applied with penalized regression methods (LASSO and ENET) when exploring relationships between common genetic variants, DNA methylation and gene expression measured in bladder tumor samples. The overall analysis flow consisted of three steps: (1) SNPs/CpGs were selected per each gene probe within 1Mb window upstream and downstream the gene; (2) LASSO and ENET were applied to assess the association between each expression probe and the selected SNPs/CpGs in three multivariable models (SNP, CPG, and Global models, the latter integrating SNPs and CPGs); and (3) the significance of each model was assessed using the permutation-based MaxT method. We identified 48 genes whose expression levels were significantly associated with both SNPs and CPGs. Importantly, 36 (75%) of them were replicated in an independent data set (TCGA) and the performance of the proposed method was checked with a simulation study. We further support our results with a biological interpretation based on an enrichment analysis. The approach we propose allows reducing computational time and is flexible and easy to implement when analyzing several types of omics data. Our results highlight the importance of integrating omics data by applying appropriate statistical strategies to discover new insights into the complex genetic mechanisms involved in disease conditions.

As an example shown in this study (http:/​/​dx.​doi.​org/​10.​1104/​pp.​113.​233932), we performed a phenotyping experiment on 33 Fernandez maize (Zea mays) plants. This energy maize cultivar was cultivated by the KWS Company. Plant images were captured using a LemnaTec 3D Scanalyzer (LemnaTec, GmbH, Wuerselen, Germany) at the Leibniz Institute of Plant Genetics and Crop Plant Research (IPK Gatersleben, Germany). Seventy-eight images were taken of every plant, of which 26 images were captured using three kinds of cameras. For each camera system, images were taken from both top view (one image) and side view (25 images). The result images were stored in PNG format (this is the JPEG compressed version of this data set). The three cameras used in the automated system are: (i) visible-light camera (Basler Pilot piA2400-17gc with resolution of 2454 x 2056 px), (ii) fluorescence camera (Basler Scout scA1400-17gc with resolution of 1390 x 1038 px) and (iii) near-infrared camera (Nir 300 with resolution of 320 x 256 px). Images were acquired daily for nine weeks. We obtained ~34000 images in total.

As an example shown in this study (http:/​/​dx.​doi.​org/​10.​1104/​pp.​113.​233932), we performed a phenotyping experiment on 33 Fernandez maize (Zea mays) plants. This energy maize cultivar was cultivated by the KWS Company. Plant images were captured using a LemnaTec 3D Scanalyzer (LemnaTec, GmbH, Wuerselen, Germany) at the Leibniz Institute of Plant Genetics and Crop Plant Research (IPK Gatersleben, Germany). Seventy-eight images were taken of every plant, of which 26 images were captured using three kinds of cameras. For each camera system, images were taken from both top view (one image) and side view (25 images). The result images were stored in PNG format (this is the JPEG compressed version of this data set). The three cameras used in the automated system are: (i) visible-light camera (Basler Pilot piA2400-17gc with resolution of 2454 x 2056 px), (ii) fluorescence camera (Basler Scout scA1400-17gc with resolution of 1390 x 1038 px) and (iii) near-infrared camera (Nir 300 with resolution of 320 x 256 px). Images were acquired daily for nine weeks. We obtained ~34000 images in total.

As an example shown in this study (http:/​/​dx.​doi.​org/​10.​1104/​pp.​113.​233932), we performed a phenotyping experiment on 33 Fernandez maize (Zea mays) plants. This energy maize cultivar was cultivated by the KWS Company. Plant images were captured using a LemnaTec 3D Scanalyzer (LemnaTec, GmbH, Wuerselen, Germany) at the Leibniz Institute of Plant Genetics and Crop Plant Research (IPK Gatersleben, Germany). Seventy-eight images were taken of every plant, of which 26 images were captured using three kinds of cameras. For each camera system, images were taken from both top view (one image) and side view (25 images). The result images were stored in PNG format (this is the JPEG compressed version of this data set). The three cameras used in the automated system are: (i) visible-light camera (Basler Pilot piA2400-17gc with resolution of 2454 x 2056 px), (ii) fluorescence camera (Basler Scout scA1400-17gc with resolution of 1390 x 1038 px) and (iii) near-infrared camera (Nir 300 with resolution of 320 x 256 px). Images were acquired daily for nine weeks. We obtained ~34000 images in total.

As an example shown in this study (http:/​/​dx.​doi.​org/​10.​1104/​pp.​113.​233932), we performed a phenotyping experiment on 33 Fernandez maize (Zea mays) plants. This energy maize cultivar was cultivated by the KWS Company. Plant images were captured using a LemnaTec 3D Scanalyzer (LemnaTec, GmbH, Wuerselen, Germany) at the Leibniz Institute of Plant Genetics and Crop Plant Research (IPK Gatersleben, Germany). Seventy-eight images were taken of every plant, of which 26 images were captured using three kinds of cameras. For each camera system, images were taken from both top view (one image) and side view (25 images). The result images were stored in PNG format (this is the JPEG compressed version of this data set). The three cameras used in the automated system are: (i) visible-light camera (Basler Pilot piA2400-17gc with resolution of 2454 x 2056 px), (ii) fluorescence camera (Basler Scout scA1400-17gc with resolution of 1390 x 1038 px) and (iii) near-infrared camera (Nir 300 with resolution of 320 x 256 px). Images were acquired daily for nine weeks. We obtained ~34000 images in total.

As an example shown in this study (http:/​/​dx.​doi.​org/​10.​1104/​pp.​113.​233932), we performed a phenotyping experiment on 33 Fernandez maize (Zea mays) plants. This energy maize cultivar was cultivated by the KWS Company. Plant images were captured using a LemnaTec 3D Scanalyzer (LemnaTec, GmbH, Wuerselen, Germany) at the Leibniz Institute of Plant Genetics and Crop Plant Research (IPK Gatersleben, Germany). Seventy-eight images were taken of every plant, of which 26 images were captured using three kinds of cameras. For each camera system, images were taken from both top view (one image) and side view (25 images). The result images were stored in PNG format (this is the JPEG compressed version of this data set). The three cameras used in the automated system are: (i) visible-light camera (Basler Pilot piA2400-17gc with resolution of 2454 x 2056 px), (ii) fluorescence camera (Basler Scout scA1400-17gc with resolution of 1390 x 1038 px) and (iii) near-infrared camera (Nir 300 with resolution of 320 x 256 px). Images were acquired daily for nine weeks. We obtained ~34000 images in total.

Table S2. Datasets of expression levels of complement proteins extracted from published publications. (XLSX 84 kb)