scholarly journals Modeling tissue-specific breakpoint proximity of structural variations from 2,382 whole-genomes to identify cancer drivers

2021 ◽  
Author(s):  
Alexander Martinez-Fundichely ◽  
Austin Dixon ◽  
Ekta Khurana
Keyword(s):  
Three Dimensional ◽  
Additive Model ◽  
Neutral Evolution ◽  
Cancer Genes ◽  
Structural Variations ◽  
Tissue Specific ◽  
Genomic Features ◽  
Interaction Terms ◽  
Whole Genomes ◽  
Genomic Regions

AbstractStructural variations (SVs) in cancer cells often impact large genomic regions with functional consequences. However, little is known about the genomic features related to the breakpoint distribution of SVs in different cancers, a prerequisite to distinguish loci under positive selection from those with neutral evolution. We developed a method that uses a generalized additive model to investigate the breakpoint proximity curves from 2,382 whole-genomes of 32 cancer types. We find that a multivariate model, which includes linear and nonlinear partial contributions of various tissue-specific features and their interaction terms, can explain up to 57% of the observed deviance of breakpoint proximity. In particular, three-dimensional genomic features such as topologically associating domains (TADs), TAD-boundaries and their interaction with other features show significant contributions. The model is validated by identification of known cancer genes and revealed putative drivers in novel cancers that have previous evidence of therapeutic relevance in other cancers.

scholarly journals SVFX: a machine-learning framework to quantify the pathogenicity of structural variants

2019 ◽  
Author(s):  
Sushant Kumar ◽  
Arif Harmanci ◽  
Jagath Vytheeswaran ◽  
Mark B. Gerstein
Keyword(s):  
Machine Learning ◽  
Large Scale ◽  
Three Dimensional ◽  
Point Mutations ◽  
Dimensional Structure ◽  
Rapid Decline ◽  
Ras Signaling ◽  
Cancer Genes ◽  
Structural Variations ◽  
Pathogenic Variants

AbstractA rapid decline in sequencing cost has made large-scale genome sequencing studies feasible. One of the fundamental goals of these studies is to catalog all pathogenic variants. Numerous methods and tools have been developed to interpret point mutations and small insertions and deletions. However, there is a lack of approaches for identifying pathogenic genomic structural variations (SVs). That said, SVs are known to play a crucial role in many diseases by altering the sequence and three-dimensional structure of the genome. Previous studies have suggested a complex interplay of genomic and epigenomic features in the emergence and distribution of SVs. However, the exact mechanism of pathogenesis for SVs in different diseases is not straightforward to decipher. Thus, we built an agnostic machine-learning-based workflow, called SVFX, to assign a “pathogenicity score” to somatic and germline SVs in various diseases. In particular, we generated somatic and germline training models, which included genomic, epigenomic, and conservation-based features for SV call sets in diseased and healthy individuals. We then applied SVFX to SVs in six different cancer cohorts and a cardiovascular disease (CVD) cohort. Overall, SVFX achieved high accuracy in identifying pathogenic SVs. Moreover, we found that predicted pathogenic SVs in cancer cohorts were enriched among known cancer genes and many cancer-related pathways (including Wnt signaling, Ras signaling, DNA repair, and ubiquitin-mediated proteolysis). Finally, we note that SVFX is flexible and can be easily extended to identify pathogenic SVs in additional disease cohorts.

scholarly journals Principal component regression in GAMLSS applied to Greek–German government bond yield spreads

2021 ◽  
pp. 1471082X2110229
Author(s):  
D. Stasinopoulos Mikis ◽  
A. Rigby Robert ◽  
Georgikopoulos Nikolaos ◽  
De Bastiani Fernanda
Keyword(s):  
Additive Model ◽  
Principal Component Regression ◽  
Principal Component ◽  
Complex Nature ◽  
Government Bond ◽  
German Government ◽  
Yield Spreads ◽  
Explanatory Variables ◽  
Interaction Terms ◽  
Bond Yield

A solution to the problem of having to deal with a large number of interrelated explanatory variables within a generalized additive model for location, scale and shape (GAMLSS) is given here using as an example the Greek–German government bond yield spreads from 25 April 2005 to 31 March 2010. Those were turbulent financial years, and in order to capture the spreads behaviour, a model has to be able to deal with the complex nature of the financial indicators used to predict the spreads. Fitting a model, using principal components regression of both main and first order interaction terms, for all the parameters of the assumed distribution of the response variable seems to produce promising results.

scholarly journals 3DIV update for 2021: a comprehensive resource of 3D genome and 3D cancer genome

2020 ◽  
Vol 49 (D1) ◽  
pp. D38-D46
Author(s):  
Kyukwang Kim ◽  
Insu Jang ◽  
Mooyoung Kim ◽  
Jinhyuk Choi ◽  
Min-Seo Kim ◽  
...  
Keyword(s):  
Cell Line ◽  
Large Scale ◽  
Three Dimensional ◽  
Cancer Cell Line ◽  
Cancer Genome ◽  
Structural Variations ◽  
3D Genome ◽  
Tightly Coupled ◽  
Regulatory Effects ◽  
The Impact

Abstract Three-dimensional (3D) genome organization is tightly coupled with gene regulation in various biological processes and diseases. In cancer, various types of large-scale genomic rearrangements can disrupt the 3D genome, leading to oncogenic gene expression. However, unraveling the pathogenicity of the 3D cancer genome remains a challenge since closer examinations have been greatly limited due to the lack of appropriate tools specialized for disorganized higher-order chromatin structure. Here, we updated a 3D-genome Interaction Viewer and database named 3DIV by uniformly processing ∼230 billion raw Hi-C reads to expand our contents to the 3D cancer genome. The updates of 3DIV are listed as follows: (i) the collection of 401 samples including 220 cancer cell line/tumor Hi-C data, 153 normal cell line/tissue Hi-C data, and 28 promoter capture Hi-C data, (ii) the live interactive manipulation of the 3D cancer genome to simulate the impact of structural variations and (iii) the reconstruction of Hi-C contact maps by user-defined chromosome order to investigate the 3D genome of the complex genomic rearrangement. In summary, the updated 3DIV will be the most comprehensive resource to explore the gene regulatory effects of both the normal and cancer 3D genome. ‘3DIV’ is freely available at http://3div.kr.

scholarly journals Three-dimensional organization of Drosophila melanogaster interphase nuclei. I. Tissue-specific aspects of polytene nuclear architecture.

1987 ◽  
Vol 104 (6) ◽  
pp. 1455-1470 ◽  
Author(s):  
M Hochstrasser ◽  
J W Sedat
Keyword(s):  
Drosophila Melanogaster ◽  
Three Dimensional ◽  
Nuclear Architecture ◽  
Close Packing ◽  
Prothoracic Gland ◽  
Cell Type ◽  
Interphase Chromosome ◽  
Tissue Specific ◽  
Spatial Domains ◽  
Four Levels

Interphase chromosome organization in four different Drosophila melanogaster tissues, covering three to four levels of polyteny, has been analyzed. The results are based primarily on three-dimensional reconstructions from unfixed tissues using a computer-based data collection and modeling system. A characteristic organization of chromosomes in each cell type is observed, independent of polyteny, with some packing motifs common to several or all tissues and others tissue-specific. All chromosomes display a right-handed coiling chirality, despite large differences in size and degree of coiling. Conversely, in each cell type, the heterochromatic centromeric regions have a unique structure, tendency to associate, and intranuclear location. The organization of condensed nucleolar chromatin is also tissue-specific. The tightly coiled prothoracic gland chromosomes are arrayed in a similar fashion to the much larger salivary gland chromosomes described previously, having polarized orientations, nonintertwined spatial domains, and close packing of the arms of each autosome, whereas hindgut and especially the unusually straight midgut chromosomes display striking departures from these regularities. Surprisingly, gut chromosomes often appear to be broken in the centric heterochromatin. Severe deformations of midgut nuclei observed during gut contractions in living larvae may account for their unusual properties. Finally, morphometric measurements of chromosome and nuclear dimensions provide insights into chromosome growth and substructure and also suggest an unexpected parallel with diploid chromatin organization.

scholarly journals Fibrin-based Bioinks: New Tricks from an Old Dog

2020 ◽  
Vol 6 (3) ◽  
Author(s):  
Anastasia Shpichka ◽  
Daria Osipova ◽  
Yuri Efremov ◽  
Polina Bikmulina ◽  
Nastasia Kosheleva ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Tissue Specific ◽  
Research Teams ◽  
The Past ◽  
Set Up

For the past 10 years, the main efforts of most bioprinting research teams have focused on creating new bioinkformulations, rather than inventing new printing set-up concepts. New tissue-specific bioinks with good printability, shapefidelity, and biocompatibility are based on “old” (well-known) biomaterials, particularly fibrin. While the interest in fibrinbased bioinks is constantly growing, it is essential to provide a framework of material’s properties and trends. This review aimsto describe the fibrin properties and application in three-dimensional bioprinting and provide a view on further developmentof fibrin-based bioinks

scholarly journals Lorentz-violating effects in three-dimensional QED

2014 ◽  
Vol 29 (22) ◽  
pp. 1450112 ◽  
Author(s):  
R. Bufalo
Keyword(s):  
Quantum Electrodynamics ◽  
Lagrangian Density ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Space Time ◽  
Nonminimal Coupling ◽  
Coupling Term ◽  
Interaction Terms ◽  
Higher Derivative ◽  
Dimensional Space Time

Inspired in discussions presented lately regarding Lorentz-violating interaction terms in B. Charneski, M. Gomes, R. V. Maluf and A. J. da Silva, Phys. Rev. D86, 045003 (2012); R. Casana, M. M. Ferreira Jr., R. V. Maluf and F. E. P. dos Santos, Phys. Lett. B726, 815 (2013); R. Casana, M. M. Ferreira Jr., E. Passos, F. E. P. dos Santos and E. O. Silva, Phys. Rev. D87, 047701 (2013), we propose here a slightly different version for the coupling term. We will consider a modified quantum electrodynamics with violation of Lorentz symmetry defined in a (2+1)-dimensional space–time. We define the Lagrangian density with a Lorentz-violating interaction, where the space–time dimensionality is explicitly taken into account in its definition. The work encompasses an analysis of this model at both zero and finite-temperature, where very interesting features are known to occur due to the space–time dimensionality. With that in mind, we expect that the space–time dimensionality may provide new insights about the radiative generation of higher-derivative terms into the action, implying in a new Lorentz-violating electrodynamics, as well the nonminimal coupling may provide interesting implications on the thermodynamical quantities.

Automatic Diagnosis of Alzheimer’s Disease Using Deep Learning Techniques

2021 ◽  
Vol 19 (11) ◽  
pp. 126-140
Author(s):  
Zahraa S. Aaraji ◽  
Hawraa H. Abbas
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Deep Learning ◽  
Data Analysis ◽  
Binary Classification ◽  
Brain Mri ◽  
Three Dimensional ◽  
Structural Variations ◽  
Automatic Feature Extraction ◽  
Multi Class Classification

Neuroimaging data analysis has attracted a great deal of attention with respect to the accurate diagnosis of Alzheimer’s disease (AD). Magnetic Resonance Imaging (MRI) scanners have thus been commonly used to study AD-related brain structural variations, providing images that demonstrate both morphometric and anatomical changes in the human brain. Deep learning algorithms have already been effectively exploited in other medical image processing applications to identify features and recognise patterns for many diseases that affect the brain and other organs; this paper extends on this to describe a novel computer aided software pipeline for the classification and early diagnosis of AD. The proposed method uses two types of three-dimensional Convolutional Neural Networks (3D CNN) to facilitate brain MRI data analysis and automatic feature extraction and classification, so that pre-processing and post-processing are utilised to normalise the MRI data and facilitate pattern recognition. The experimental results show that the proposed approach achieves 97.5%, 82.5%, and 83.75% accuracy in terms of binary classification AD vs. cognitively normal (CN), CN vs. mild cognitive impairment (MCI) and MCI vs. AD, respectively, as well as 85% accuracy for multi class-classification, based on publicly available data sets from the Alzheimer’s disease Neuroimaging Initiative (ADNI).

scholarly journals Microribbons composed of directionally self-assembled nanoflakes as highly stretchable ionic neural electrodes

2020 ◽  
Vol 117 (26) ◽  
pp. 14667-14675 ◽  
Author(s):  
Mingchao Zhang ◽  
Rui Guo ◽  
Ke Chen ◽  
Yiliang Wang ◽  
Jiali Niu ◽  
...  
Keyword(s):  
Self Assembly ◽  
Structural Variation ◽  
Three Dimensional ◽  
Biological Tissues ◽  
Superior Performance ◽  
Ionic Conductors ◽  
Structural Variations ◽  
Neural Electrodes ◽  
Self Assembled

Many natural materials possess built-in structural variation, endowing them with superior performance. However, it is challenging to realize programmable structural variation in self-assembled synthetic materials since self-assembly processes usually generate uniform and ordered structures. Here, we report the formation of asymmetric microribbons composed of directionally self-assembled two-dimensional nanoflakes in a polymeric matrix during three-dimensional direct-ink printing. The printed ribbons with embedded structural variations show site-specific variance in their mechanical properties. Remarkably, the ribbons can spontaneously transform into ultrastretchable springs with controllable helical architecture upon stimulation. Such springs also exhibit superior nanoscale transport behavior as nanofluidic ionic conductors under even ultralarge tensile strains (>1,000%). Furthermore, to show possible real-world uses of such materials, we demonstrate in vivo neural recording and stimulation using such springs in a bullfrog animal model. Thus, such springs can be used as neural electrodes compatible with soft and dynamic biological tissues.

scholarly journals Different Benzendicarboxylate-Directed Structural Variations and Properties of Four New Porous Cd(II)-Pyridyl-Triazole Coordination Polymers

2020 ◽  
Vol 8 ◽  
Author(s):  
Ying Zhao ◽  
Jin Jing ◽  
Ning Yan ◽  
Min-Le Han ◽  
Guo-Ping Yang ◽  
...  
Keyword(s):  
Solid State ◽  
Coordination Polymers ◽  
Three Dimensional ◽  
Two Dimensional ◽  
Gas Sorption ◽  
Structural Variations ◽  
Benzenedicarboxylic Acid ◽  
Topological Framework ◽  
The Stability

Four new different porous crystalline Cd(II)-based coordination polymers (CPs), i. e., [Cd(mdpt)2]·2H2O (1), [Cd2(mdpt)2(m-bdc)(H2O)2] (2), [Cd(Hmdpt)(p-bdc)]·2H2O (3), and [Cd3(mdpt)2(bpdc)2]·2.5NMP (4), were obtained successfully by the assembly of Cd(II) ions and bitopic 3-(3-methyl-2-pyridyl)-5-(4-pyridyl)-1,2,4-triazole (Hmdpt) in the presence of various benzendicarboxylate ligands, i.e., 1,3/1,4-benzenedicarboxylic acid (m-H2bdc, p-H2bdc) and biphenyl-4,4′-bicarboxylate (H2bpdc). Herein, complex 1 is a porous 2-fold interpenetrated four-connected 3D NbO topological framework based on the mdpt− ligand; 2 reveals a two-dimensional (2D) hcb network. Interestingly, 3 presents a three-dimensional (3D) rare interpenetrated double-insertion supramolecular net via 2D ···ABAB··· layers and can be viewed as an fsh topological net, while complex 4 displays a 3D sqc117 framework. Then, the different gas sorption performances were carried out carefully for complexes 1 and 4, the results of which showed 4 has preferable sorption than that of 1 and can be the potential CO2 storage and separation material. Furthermore, the stability and luminescence of four complexes were performed carefully in the solid state.

scholarly journals A Novel Method for Electrospinning Nanofibrous 3-D Structures

Fibers ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 27 ◽  
Author(s):  
Daniela Lubasova ◽  
Anil N. Netravali
Keyword(s):  
Three Dimensional ◽  
Development Trend ◽  
Proof Of Concept ◽  
Structural Variations ◽  
Fiber Volume ◽  
Electrospinning Technique ◽  
Web Structure ◽  
Fiber Spacing ◽  
Novel Method ◽  
Volume Unit

The fast and precise fabrication of three-dimensional (3-D) structures made of nanofibers is an important development trend in the electrospinning technique. This paper describes a new and facile method of electrospinning to fabricate nanofibrous 3-D structures. The nanofibrous 3-D structures can be engineered to have the desired layer thicknesses, where the fiber spacing, density (i.e., fiber volume/unit volume), as well as shape of the structure may be controlled. While innumerable structural variations are possible with this method, this paper discusses, as proof-of-concept, a few cases that illustrate how 3-D nanofiber webs can be made for filtration application. Computerized automation of the method will make it possible to build almost any 3-D web structure suitable for a myriad of applications including ultra-light-weight insulation and scaffolds for hydrogel preparation and tissue.

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