scholarly journals MorphOT: transport-based interpolation between EM maps with UCSF ChimeraX

2020 ◽  
Author(s):  
Arthur Ecoffet ◽  
Frédéric Poitevin ◽  
Khanh Dao Duc
Keyword(s):  
Optimal Transport ◽  
Three Dimensional ◽  
Linear Interpolation ◽  
The Other ◽  
Supplementary Information ◽  
Conformational Heterogeneity ◽  
Supplementary Data ◽  
Image Dataset ◽  
Standard Linear ◽  
Unique Potential

Abstract Motivation Cryogenic electron microscopy (cryo-EM) offers the unique potential to capture conformational heterogeneity, by solving multiple three-dimensional classes that co-exist within a single cryo-EM image dataset. To investigate the extent and implications of such heterogeneity, we propose to use an optimal-transport-based metric to interpolate barycenters between EM maps and produce morphing trajectories. Results While standard linear interpolation mostly fails to produce realistic transitions, our method yields continuous trajectories that displace densities to morph one map into the other, instead of blending them. Availability and implementation Our method is implemented as a plug-in for ChimeraX called MorphOT, which allows the use of both CPU or GPU resources. The code is publicly available on GitHub (https://github.com/kdd-ubc/MorphOT.git), with documentation containing tutorial and datasets. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals MorphOT: Transport-based interpolation between EM maps with UCSF ChimeraX

2020 ◽  
Author(s):  
Arthur Ecoffet ◽  
Frédéric Poitevin ◽  
Khanh Dao Duc
Keyword(s):  
Electron Microscopy ◽  
Optimal Transport ◽  
Linear Interpolation ◽  
The Other ◽  
Conformational Heterogeneity ◽  
Link Type ◽  
Image Dataset ◽  
Standard Linear ◽  
Unique Potential

AbstractMotivationCryogenic Electron-Microscopy offers the unique potential to capture conformational heterogeneity, by solving multiple 3D classes that co-exist within a single cryo-EM image dataset. To investigate the extent and implications of such heterogeneity, we propose to use an optimal-transport based metric to interpolate barycenters between EM maps and produce morphing trajectories. While standard linear interpolation mostly fails to produce realistic transitions, our method yields continuous trajectories that displace densities to morph one map into the other, instead of blending them.ImplementationOur method is implemented as a plug-in for ChimeraX called MorphOT, which allows the use of both CPU or GPU resources. The code is publicly available on GitHub (https://github.com/kdd-ubc/MorphOT.git), with documentation containing tutorial and [email protected]

A dynamic recursive feature elimination framework (dRFE) to further refine a set of OMIC biomarkers

2021 ◽  
Author(s):  
Yuanyuan Han ◽  
Lan Huang ◽  
Fengfeng Zhou
Keyword(s):  
Experimental Data ◽  
Feature Selection ◽  
The Other ◽  
Supplementary Information ◽  
Recursive Feature Elimination ◽  
Supplementary Data ◽  
Selection Algorithm ◽  
Feature Selection Algorithm ◽  
Class Labels ◽  
Selection Algorithms

Abstract Motivation A feature selection algorithm may select the subset of features with the best associations with the class labels. The recursive feature elimination (RFE) is a heuristic feature screening framework and has been widely used to select the biological OMIC biomarkers. This study proposed a dynamic recursive feature elimination (dRFE) framework with more flexible feature elimination operations. The proposed dRFE was comprehensively compared with 11 existing feature selection algorithms and five classifiers on the eight difficult transcriptome datasets from a previous study, the ten newly collected transcriptome datasets and the five methylome datasets. Results The experimental data suggested that the regular RFE framework did not perform well, and dRFE outperformed the existing feature selection algorithms in most cases. The dRFE-detected features achieved Acc = 1.0000 for the two methylome datasets GSE53045 and GSE66695. The best prediction accuracies of the dRFE-detected features were 0.9259, 0.9424 and 0.8601 for the other three methylome datasets GSE74845, GSE103186 and GSE80970, respectively. Four transcriptome datasets received Acc = 1.0000 using the dRFE-detected features, and the prediction accuracies for the other six newly collected transcriptome datasets were between 0.6301 and 0.9917. Availability and implementation The experiments in this study are implemented and tested using the programming language Python version 3.7.6. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Prediction of protein-binding residues: dichotomy of sequence-based methods developed using structured complexes versus disordered proteins

2020 ◽  
Vol 36 (18) ◽  
pp. 4729-4738 ◽  
Author(s):  
Jian Zhang ◽  
Sina Ghadermarzi ◽  
Lukasz Kurgan
Keyword(s):  
Protein Binding ◽  
The Other ◽  
Disordered Proteins ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Protein Partners ◽  
Structure Disorder ◽  
Binding Residues ◽  
The Cross ◽  
Protein Nucleic Acid

Abstract Motivation There are over 30 sequence-based predictors of the protein-binding residues (PBRs). They use either structure-annotated or disorder-annotated training datasets, potentially creating a dichotomy where the structure-/disorder-specific models may not be able to cross-over to accurately predict the other type. Moreover, the structure-trained predictors were shown to substantially cross-predict PBRs among residues that interact with non-protein partners (nucleic acids and small ligands). We address these issues by performing first-of-its-kind comparative study of a representative collection of disorder- and structure-trained predictors using a comprehensive benchmark set with the structure- and disorder-derived annotations of PBRs (to analyze the cross-over) and the protein-, nucleic acid- and small ligand-binding proteins (to study the cross-predictions). Results Three predictors provide accurate results: SCRIBER, ANCHOR and disoRDPbind. Some of the structure-trained methods make accurate predictions on the structure-annotated proteins. Similarly, the disorder-trained predictors predict well on the disorder-annotated proteins. However, the considered predictors generally fail to cross-over, with the exception of SCRIBER. Our study also reveals that virtually all methods substantially cross-predict PBRs, except for SCRIBER for the structure-annotated proteins and disoRDPbind for the disorder-annotated proteins. We formulate a novel hybrid predictor, hybridPBRpred, that combines results produced by disoRDPbind and SCRIBER to accurately predict disorder- and structure-annotated PBRs. HybridPBRpred generates accurate results that cross-over structure- and disorder-annotated proteins and produces relatively low amount of cross-predictions, offering an accurate alternative to predict PBRs. Availability and implementation HybridPBRpred webserver, benchmark dataset and supplementary information are available at http://biomine.cs.vcu.edu/servers/hybridPBRpred/. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals A Fast Segmentation and Efficient Slice Reconstruction Technique for Head CT Images

2019 ◽  
Vol 28 (4) ◽  
pp. 533-547
Author(s):  
A.A. Haseena Thasneem ◽  
M. Mohamed Sathik ◽  
R. Mehaboobathunnisa
Keyword(s):  
Three Dimensional ◽  
Human Head ◽  
Structural Similarity ◽  
Linear Interpolation ◽  
Reconstruction Technique ◽  
Data Sets ◽  
Storage Space ◽  
Minimal Impact ◽  
Space And Time ◽  
Standard Linear

Abstract The three-dimensional (3D) reconstruction of medical images usually requires hundreds of two-dimensional (2D) scan images. Segmentation, an obligatory part in reconstruction, needs to be performed for all the slices consuming enormous storage space and time. To reduce storage space and time, this paper proposes a three-stage procedure, namely, slice selection, segmentation and interpolation. The methodology will have the potential to 3D reconstruct the human head from minimum selected slices. The first stage of slice selection is based on structural similarity measurement, discarding the most similar slices with none or minimal impact on details. The second stage of segmentation of the selected slices is performed using our proposed phase-field segmentation method. Validation of our segmentation results is done via comparison with other deformable models, and results show that the proposed method provides fast and accurate segmentation. The third stage of interpolation is based on modified curvature registration-based interpolation, and it is applied to re-create the discarded slices. This method is compared to both standard linear interpolation and registration-based interpolation in 100 tomographic data sets. Results show that the modified curvature registration-based interpolation reconstructs missing slices with 96% accuracy and shows an improvement in sensitivity (95.802%) on par with specificity (95.901%).

Three-Dimensional Reconstruction of Two Forms of the Chaperonin GRO EL

1990 ◽  
Vol 48 (1) ◽  
pp. 258-259
Author(s):  
J.L. Carrascosa ◽  
G. Abella ◽  
S. Marco ◽  
M. Muyal ◽  
J.M. Carazo
Keyword(s):  
Three Dimensional ◽  
The Other ◽  
Two Dimensional ◽  
Series Method ◽  
Three Dimensional Reconstruction ◽  
Structural Components ◽  
E Coli ◽  
Dimensional Reconstruction ◽  
Morphogenetic Factors ◽  
Tilt Series

Chaperonins are a class of proteins characterized by their role as morphogenetic factors. They trantsiently interact with the structural components of certain biological aggregates (viruses, enzymes etc), promoting their correct folding, assembly and, eventually transport. The groEL factor from E. coli is a conspicuous member of the chaperonins, as it promotes the assembly and morphogenesis of bacterial oligomers and/viral structures.We have studied groEL-like factors from two different bacteria:E. coli and B.subtilis. These factors share common morphological features , showing two different views: one is 6-fold, while the other shows 7 morphological units. There is also a correlation between the presence of a dominant 6-fold view and the fact of both bacteria been grown at low temperature (32°C), while the 7-fold is the main view at higher temperatures (42°C). As the two-dimensional projections of groEL were difficult to interprete, we studied their three-dimensional reconstruction by the random conical tilt series method from negatively stained particles.

An Efficient Multiple Description Coding for Multi-View Video Based on the Correlation of Spatial Polyphase Transformed Subsequences

2019 ◽  
Vol 63 (5) ◽  
pp. 50401-1-50401-7 ◽  
Author(s):  
Jing Chen ◽  
Jie Liao ◽  
Huanqiang Zeng ◽  
Canhui Cai ◽  
Kai-Kuang Ma
Keyword(s):  
Video Transmission ◽  
Video Sequence ◽  
Three Dimensional ◽  
The Other ◽  
Multiple Description Coding ◽  
Multiple Description ◽  
Prediction Mode ◽  
Gradient Based ◽  
Directional Interpolation ◽  
Description Coding

Abstract For a robust three-dimensional video transmission through error prone channels, an efficient multiple description coding for multi-view video based on the correlation of spatial polyphase transformed subsequences (CSPT_MDC_MVC) is proposed in this article. The input multi-view video sequence is first separated into four subsequences by spatial polyphase transform and then grouped into two descriptions. With the correlation of macroblocks in corresponding subsequence positions, these subsequences should not be coded in completely the same way. In each description, one subsequence is directly coded by the Joint Multi-view Video Coding (JMVC) encoder and the other subsequence is classified into four sets. According to the classification, the indirectly coding subsequence selectively employed the prediction mode and the prediction vector of the counter directly coding subsequence, which reduces the bitrate consumption and the coding complexity of multiple description coding for multi-view video. On the decoder side, the gradient-based directional interpolation is employed to improve the side reconstructed quality. The effectiveness and robustness of the proposed algorithm is verified by experiments in the JMVC coding platform.

scholarly journals ccNetViz: a WebGL-based JavaScript library for visualization of large networks

2020 ◽  
Vol 36 (16) ◽  
pp. 4527-4529
Author(s):  
Ales Saska ◽  
David Tichy ◽  
Robert Moore ◽  
Achilles Rasquinha ◽  
Caner Akdas ◽  
...  
Keyword(s):  
Systems Biology ◽  
Complex Networks ◽  
Open Source ◽  
High Speed ◽  
A Priori ◽  
Supplementary Information ◽  
Network Visualization ◽  
Supplementary Data ◽  
Web Based ◽  
Flow Of Information

Abstract Summary Visualizing a network provides a concise and practical understanding of the information it represents. Open-source web-based libraries help accelerate the creation of biologically based networks and their use. ccNetViz is an open-source, high speed and lightweight JavaScript library for visualization of large and complex networks. It implements customization and analytical features for easy network interpretation. These features include edge and node animations, which illustrate the flow of information through a network as well as node statistics. Properties can be defined a priori or dynamically imported from models and simulations. ccNetViz is thus a network visualization library particularly suited for systems biology. Availability and implementation The ccNetViz library, demos and documentation are freely available at http://helikarlab.github.io/ccNetViz/. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Epidemiological modeling in StochSS Live!

2021 ◽  
Author(s):  
Richard Jiang ◽  
Bruno Jacob ◽  
Matthew Geiger ◽  
Sean Matthew ◽  
Bryan Rumsey ◽  
...  
Keyword(s):  
Stochastic Model ◽  
Epidemiological Model ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Web Based ◽  
Epidemiological Modeling ◽  
Modeling Simulation ◽  
Wide Range ◽  
Biochemical Systems

Abstract Summary We present StochSS Live!, a web-based service for modeling, simulation and analysis of a wide range of mathematical, biological and biochemical systems. Using an epidemiological model of COVID-19, we demonstrate the power of StochSS Live! to enable researchers to quickly develop a deterministic or a discrete stochastic model, infer its parameters and analyze the results. Availability and implementation StochSS Live! is freely available at https://live.stochss.org/ Supplementary information Supplementary data are available at Bioinformatics online.

KEC: unique sequence search by K-mer exclusion

2021 ◽  
Author(s):  
Pavel Beran ◽  
Dagmar Stehlíková ◽  
Stephen P Cohen ◽  
Vladislav Čurn
Keyword(s):  
Amino Acid ◽  
Nucleic Acid ◽  
Source Code ◽  
Unique Sequence ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Laptop Computers ◽  
Sequence Search ◽  
Target Sequences ◽  
Cross Reference

Abstract Summary Searching for amino acid or nucleic acid sequences unique to one organism may be challenging depending on size of the available datasets. K-mer elimination by cross-reference (KEC) allows users to quickly and easily find unique sequences by providing target and non-target sequences. Due to its speed, it can be used for datasets of genomic size and can be run on desktop or laptop computers with modest specifications. Availability and implementation KEC is freely available for non-commercial purposes. Source code and executable binary files compiled for Linux, Mac and Windows can be downloaded from https://github.com/berybox/KEC. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals On the Kirchhoff-Love Hypothesis (Revised and Vindicated)

2021 ◽  
Author(s):  
Olivier Ozenda ◽  
Epifanio G. Virga
Keyword(s):  
Free Energy ◽  
Dimension Reduction ◽  
Three Dimensional ◽  
Energy Functional ◽  
The Other ◽  
Variational Model ◽  
Two Dimensional ◽  
Elastic Plates ◽  
Kinematic Constraint ◽  
Free Energy Functional

AbstractThe Kirchhoff-Love hypothesis expresses a kinematic constraint that is assumed to be valid for the deformations of a three-dimensional body when one of its dimensions is much smaller than the other two, as is the case for plates. This hypothesis has a long history checkered with the vicissitudes of life: even its paternity has been questioned, and recent rigorous dimension-reduction tools (based on standard $\varGamma $ Γ -convergence) have proven to be incompatible with it. We find that an appropriately revised version of the Kirchhoff-Love hypothesis is a valuable means to derive a two-dimensional variational model for elastic plates from a three-dimensional nonlinear free-energy functional. The bending energies thus obtained for a number of materials also show to contain measures of stretching of the plate’s mid surface (alongside the expected measures of bending). The incompatibility with standard $\varGamma $ Γ -convergence also appears to be removed in the cases where contact with that method and ours can be made.

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