Incorrect Topology Research Articles

TopoDoE: a design of experiment strategy for selection and refinement in ensembles of executable gene regulatory networks

BackgroundInference of Gene Regulatory Networks (GRNs) is a difficult and long-standing question in Systems Biology. Numerous approaches have been proposed with the latest methods exploring the richness of single-cell data. One of the current difficulties lies in the fact that many methods of GRN inference do not result in one proposed GRN but in a collection of plausible networks that need to be further refined. In this work, we present a Design of Experiment strategy to use as a second stage after the inference process. It is specifically fitted for identifying the next most informative experiment to perform for deciding between multiple network topologies, in the case where proposed GRNs are executable models. This strategy first performs a topological analysis to reduce the number of perturbations that need to be tested, then predicts the outcome of the retained perturbations by simulation of the GRNs and finally compares predictions with novel experimental data.ResultsWe apply this method to the results of our divide-and-conquer algorithm called WASABI, adapt its gene expression model to produce perturbations and compare our predictions with experimental results. We show that our networks were able to produce in silico predictions on the outcome of a gene knock-out, which were qualitatively validated for 48 out of 49 genes. Finally, we eliminate as many as two thirds of the candidate networks for which we could identify an incorrect topology, thus greatly improving the accuracy of our predictions.ConclusionThese results both confirm the inference accuracy of WASABI and show how executable gene expression models can be leveraged to further refine the topology of inferred GRNs. We hope this strategy will help systems biologists further explore their data and encourage the development of more executable GRN models.

Anatomically plausible segmentations: Explicitly preserving topology through prior deformations

Since the rise of deep learning, new medical segmentation methods have rapidly been proposed with extremely promising results, often reporting marginal improvements on the previous state-of-the-art (SOTA) method. However, on visual inspection errors are often revealed, such as topological mistakes (e.g. holes or folds), that are not detected using traditional evaluation metrics. Incorrect topology can often lead to errors in clinically required downstream image processing tasks. Therefore, there is a need for new methods to focus on ensuring segmentations are topologically correct. In this work, we present TEDS-Net: a segmentation network that preserves anatomical topology whilst maintaining segmentation performance that is competitive with SOTA baselines. Further, we show how current SOTA segmentation methods can introduce problematic topological errors. TEDS-Net achieves anatomically plausible segmentation by using learnt topology-preserving fields to deform a prior. Traditionally, topology-preserving fields are described in the continuous domain and begin to break down when working in the discrete domain. Here, we introduce additional modifications that more strictly enforce topology preservation. We illustrate our method on an open-source medical heart dataset, performing both single and multi-structure segmentation, and show that the generated fields contain no folding voxels, which corresponds to full topology preservation on individual structures whilst vastly outperforming the other baselines on overall scene topology. The code is available at: https://github.com/mwyburd/TEDS-Net.

Filtration of Gene Trees From 9,000 Exons, Introns, and UCEs Disentangles Conflicting Phylogenomic Relationships in Tree Frogs (Hylidae).

An emerging challenge in interpreting phylogenomic data sets is that concatenation and multi-species coalescent summary species tree approaches may produce conflicting results. Concatenation is problematic because it can strongly support an incorrect topology when incomplete lineage sorting (ILS) results in elevated gene-tree discordance. Conversely, summary species tree methods account for ILS to recover the correct topology, but these methods do not account for erroneous gene trees ("EGTs") resulting from gene tree estimation error (GTEE). Third, site-based and full-likelihood methods promise to alleviate GTEE as these methods use the sequence data from alignments. To understand the impact of GTEE on species tree estimation in Hylidae tree frogs, we use an expansive data set of ∼9,000 exons, introns, and ultra-conserved elements and initially found conflict between all three types of analytical methods. We filtered EGTs using alignment metrics that could lead to GTEE (length, parsimony-informative sites, and missing data) and found that removing shorter, less informative alignments reconciled the conflict between concatenation and summary species tree methods with increased gene concordance, with the filtered topologies matching expected results from past studies. Contrarily, site-based and full-likelihood methods were mixed where one method was consistent with past studies and the other varied markedly. Critical to other studies, these results suggest a widespread conflation of ILS and GTEE, where EGTs rather than ILS are driving discordance. Finally, we apply these recommendations to an R package named PhyloConfigR, which facilitates phylogenetic software setup, summarizes alignments, and provides tools for filtering alignments and gene trees.

The Complete Mitochondrial Genome of Northeast Asian Rove Beetle, Lordithon arcuatus (Solsky, 1871) and Performance of Site-Specific Mixture Models in Building the Mitogenomic Phylogeny of Staphylinidae (Insecta: Coleoptera)

Lordithon species are typically mushroom-dwelling rove beetles that devour maggots. This study presents the mitogenome of a Lordithon arcuatus specimen that was procured from Changbai Mountain in the Jilin Province of China. The mitogenome is 18,290 bp long and comprises 13 protein-coding genes, 22 tRNAs, and 2 rRNAs. The base composition of the mitogenome is as follows: A = 38.80%, T = 37.93%, G = 8.94%, and C = 14.32%. Maximum likelihood and Bayesian phylogenetic trees were constructed using 68 representative staphylinid species, which showed that Lordithon, Bolitobius, and Ischnosoma form a stable and fully supported Mycetoporinae clade, whereas there was no consensus regarding the relationships among Tachyporinae taxa. Additionally, the performance of site-specific mixture models for inferring the phylogeny of staphylinids using mitogenomic data was assessed. The results suggest that heterotachy models should be used with caution, as they may result in incorrect topology with delusive precedence in AIC- or BIC-based model selection.

Cryo-EM reveals an entangled kinetic trap in the folding of a catalytic RNA.

Functional RNAs fold through complex pathways that can contain misfolded “kinetic traps.” A complete model of RNA folding requires understanding the formation of these misfolded states, but they are difficult to characterize because of their transient and potentially conformationally dynamic nature. We used cryo–electron microscopy (cryo-EM) to visualize a long-lived misfolded state in the folding pathway of the Tetrahymena thermophila group I intron, a paradigmatic RNA structure-function model system. The structure revealed how this state forms native-like secondary structure and tertiary contacts but contains two incorrectly crossed strands, consistent with a previous model. This incorrect topology mispositions a critical catalytic domain and cannot be resolved locally as extensive refolding is required. This work provides a structural framework for interpreting decades of biochemical and functional studies and demonstrates the power of cryo-EM for the exploration of RNA folding pathways.

Nonadiabatic dynamics with spin-flip vs linear-response time-dependent density functional theory: A case study for the protonated Schiffbase C5H6NH2.

Nonadiabatic trajectory surface hopping simulations are reported for trans-C5H6NH2 +, a model of the rhodopsinchromophore, using the augmented fewest-switches algorithm. Electronic structure calculations were performed using time-dependent density functional theory (TDDFT) in both its conventional linear-response (LR) and its spin-flip (SF) formulations. In the SF-TDDFT case, spin contamination in the low-lying singlet states is removed by projecting out the lowest triplet component during iterative solution of the TDDFT eigenvalue problem. The results show that SF-TDDFT qualitatively describes the photoisomerization of trans-C5H6NH2 +, with favorable comparison to previous studies using multireference electronic structure methods. In contrast, conventional LR-TDDFT affords qualitatively different photodynamics due to an incorrect excited-state potential surface near the Franck-Condon region. In addition, the photochemistry (involving pre-twisting of the central double bond) appears to be different for SF- and LR-TDDFT, which may be a consequence of different conical intersection topographies afforded by these two methods. The present results contrast with previous surface-hopping studies suggesting that the LR-TDDFT method's incorrect topology around S1/S0 conical intersections is immaterial to the photodynamics.

Large-scale natural fracture network patterns: Insights from automated mapping in the Lilstock (Bristol Channel) limestone outcrops

The Lilstock outcrop in the southern Bristol Channel provides exceptional exposures of several limestone beds displaying stratabound fracture networks, providing the opportunity to create a very large, complete, and ground-truthed fracture model. Here we present the result of automated fracture extraction of high-resolution photogrammetric images (0.9 cm/pixel) of the full outcrop, obtained using an unmanned aerial vehicle, to obtain a spatially extensive, full-resolution map of the complete fracture network with nearly 350,000 ground-truthed fractures. We developed graph-based functions to resolve some common issues that arise in automatic fracture tracing such as incomplete traces, incorrect topology, artificial fragmentation, and linking of fracture segments to generate geologically significant trace interpretations. The fracture networks corresponding to different regions within the outcrop are compared using several network metrics and the results indicate both inter- and intra-network (layer to layer) structural variabilities. The dataset is a valuable benchmark in the study of large-scale natural fracture networks and its extension to stochastic network generation in geomodelling. The dataset also highlights the intrinsic spatial variation in natural fracture networks that can occur even in weakly-deformed rocks over relatively short length scales of tens of metres.

Comparative genomics confirms a rare melioidosis human-to-human transmission event and reveals incorrect phylogenomic reconstruction due to polyclonality.

Human-to-human transmission of the melioidosis bacterium, Burkholderia pseudomallei , is exceedingly rare, with only a handful of suspected cases documented to date. Here, we used whole-genome sequencing (WGS) to characterize one such unusual B. pseudomallei transmission event, which occurred between a breastfeeding mother with mastitis and her child. Two strains corresponding to multilocus sequence types (STs)-259 and -261 were identified in the mother’s sputum from both the primary culture sweep and in purified colonies, confirming an unusual polyclonal infection in this patient. In contrast, primary culture sweeps of the mother’s breast milk and the child’s cerebrospinal fluid and blood samples contained only ST-259, indicating monoclonal transmission to the child. Analysis of purified ST-259 isolates showed no genetic variation between mother and baby isolates, providing the strongest possible evidence of B. pseudomallei human-to-human transmission, probably via breastfeeding. Next, phylogenomic analysis of all isolates, including the mother’s mixed ST-259/ST-261 sputum sample, was performed to investigate the effects of mixtures on phylogenetic inference. Inclusion of this mixture caused a dramatic reduction in the number of informative SNPs, resulting in branch collapse of ST-259 and ST-261 isolates, and several instances of incorrect topology in a global B. pseudomallei phylogeny, resulting in phylogenetic incongruence. Although phylogenomics can provide clues about the presence of mixtures within WGS datasets, our results demonstrate that this methodology can lead to phylogenetic misinterpretation if mixed genomes are not correctly identified and omitted. Using current bioinformatic tools, we demonstrate a robust method for bacterial mixture identification and strain parsing that avoids these pitfalls.

A Statistical Learning-Based Algorithm for Topology Verification in Natural Gas Networks Based on Noisy Sensor Measurements

Accurate knowledge of natural gas network topology is critical for the proper operation of natural gas networks. Failures, physical attacks, and cyber attacks can cause the actual natural gas network topology to differ from what the operator believes to be present. Incorrect topology information misleads the operator to apply inappropriate control causing damage and lack of gas supply. Several methods for verifying the topology have been suggested in the literature for electrical power distribution networks, but we are not aware of any publications for natural gas networks. In this paper, we develop a useful topology verification algorithm for natural gas networks based on modifying a general known statistics-based approach to eliminate serious limitations for this application while maintaining good performance. We prove that the new algorithm is equivalent to the original statistics-based approach for a sufficiently large number of sensor observations. We provide new closed-form expressions for the asymptotic performance that are shown to be accurate for the typical number of sensor observations required to achieve reliable performance.

The Simplest Possible Approach for Simulating S0- S1 Conical Intersections with DFT/TDDFT: Adding One Doubly Excited Configuration.

A simple combination of density functional theory/time-dependent density functional theory (DFT/TDDFT) and configuration interaction is presented to fix the incorrect topology of the S0- S1 conical intersection (CI) and allow a description of bond making and bond breaking in photoinduced dynamics. The proposed TDDFT-1D method includes one lone optimized doubly excited configuration in addition to the DFT/TDDFT singly excited states within the context of a large configuration interaction Hamiltonian. Results for ethylene and stilbene are provided to demonstrate that this ansatz can yield physically meaningful potential energy surfaces near S0- S1 avoided crossings without changing the vertical excitation energies far from the relevant crossings. We also investigate the famous linear water example to show that the algorithm calculates the correct topology of the S0- S1 CI and yields the correct geometric phase.

Atomic-Level Protein Structure Refinement Using Fragment-Guided Molecular Dynamics Conformation Sampling

One of critical difficulties of molecular dynamics (MD)simulations in protein structure refinement is that thephysics-based energy landscape lacksa middle-range funnel to guide nonnative conformations toward near-native states. We propose to use the target model as a probe to identify fragmental analogs from PDB. The distance maps are then used to reshape the MD energy funnel. The protocol was tested on 181 benchmarking and 26 CASP targets. It was found that structure models of correct folds with TM-score >0.5 can be often pulled closer to native with higher GDT-HA score, but improvement for the models of incorrect folds (TM-score <0.5) are much less pronounced. These data indicate that template-based fragmental distance maps essentially reshaped the MD energy landscape from golf-course-like to funnel-like ones in the successfully refined targets with a radius of TM-score ∼0.5. These results demonstrate a new avenue to improve high-resolution structures by combining knowledge-based template information with physics-based MD simulations.

The effect of incongruence on molecular dates

ABSTRACTDespite what is known about processes that can cause topological incongruence among datasets, combined analysis of concatenated datasets (simultaneous analysis) without examination of congruence is still advocated and practiced. Although the danger in such cases of inferring the incorrect topology is known (and sometimes ignored), here I examine an under‐appreciated effect of the combined analysis of incongruent datasets on molecular date inferences. Using simulated character matrices, a bias towards either increased or decreased dates is demonstrated that increases in its effect with greater proportion of incongruent characters. A general prediction is made regarding the behaviour of molecular date estimates based on the phylogenetic position of taxa that are incongruent. This prediction is borne out in a case study using real data from incongruent nuclear genes in Medicago (Fabaceae).

Ten-Microsecond Molecular Dynamics Simulation of a Fast-Folding WW Domain

All-atom molecular dynamics (MD) simulations of protein folding allow analysis of the folding process at an unprecedented level of detail. Unfortunately, such simulations have not yet reached their full potential both due to difficulties in sufficiently sampling the microsecond timescales needed for folding, and because the force field used may yield neither the correct dynamical sequence of events nor the folded structure. The ongoing study of protein folding through computational methods thus requires both improvements in the performance of molecular dynamics programs to make longer timescales accessible, and testing of force fields in the context of folding simulations. We report a ten-microsecond simulation of an incipient downhill-folding WW domain mutant along with measurement of a molecular time and activated folding time of 1.5 microseconds and 13.3 microseconds, respectively. The protein simulated in explicit solvent exhibits several metastable states with incorrect topology and does not assume the native state during the present simulations.

Ancient paralogy in the cpDNA trnL‐F region in Annonaceae: implications for plant molecular systematics

The plastid trnL-F region has proved useful in molecular phylogenetic studies addressing diverse evolutionary questions from biogeographic history to character evolution in a broad range of plant groups. An important assumption for phylogenetic reconstruction is that data used in combined analyses contain the same phylogenetic signal. The trnL-F region is often used in combined analyses of multiple chloroplast markers. These markers are assumed to contain congruent phylogenetic signal due to lack of recombination. Here we show that trnL-F sequences display a phylogenetic signal conflicting with that of other chloroplast markers in Annonaceae, and we demonstrate that this conflict results from ancient paralogy. TrnL-F copy 2 diverged from trnL-F copy 1 (as used in family-wide phylogenetic analyses) in a direct ancestor of the Annonaceae. Although this divergence dates back 88 million years or more, the exons of both copies appear to be intact. In this case, assuming that (putative) chloroplast markers contain the same phylogenetic signal results in an incorrect topology and an incorrect estimate of ages. Our study demonstrates that researchers should be cautious when interpreting gene phylogenies, irrespective of the genome from which they are presumed to have been sampled.

Tree Fitting: Topological Recognition from Ordinary Least-Squares Edge Length Estimates

Distance methods play a central role in the field of phylogeny reconstruction, providing fast, efficient algorithms which yield reliable trees. A leading method in this field is the minimum evolution (ME) method, which selects the topology whose size is minimized when edge lengths have been selected for each topology via an ordinary least-squares (OLS) criterion. Vach and Degens (1991) have demonstrated that this OLS solution can be found by constraining edge lengths for a given topology such that average distances across each split in the tree metric equal those of the input metric. In this work we consider the vector space of tree metrics with regard to a basis generated by split average distances. This algebraic structure leads us to a conjecture regarding the edge weights of OLS tree fitting. We conjecture that if we fit a tree metric to an incorrect topology, the incorrectness will be detectable via a negative length assignment to one of the edges corresponding to a split in the test topology which is not shared by the true topology. This conjecture is proven for topologies sufficiently close to the true topology, and simulations suggest that it may be true in a more general case. We consider the durability of this topological signal in the presence of noisy sampling.

Towards ITS Map Database Interoperability—Database Error and Rectification

One of the impediments to the implementation of ITS is the lack of map database interoperability. Centreline databases are available from a number of sources, but few were designed specifically for ITS. Consequently there are a variety of problems—coordinate inaccuracy, errors of omission and commission, missing or wrong street names, incorrect topology—that are compounded when communicating parties use databases from different vendors. Many ITS applications (e.g., emergency response, ATIS) rely on the exchange of messages in which location is a component. Map error and interoperability problems can result in a variety of practical difficulties, from inappropriate vehicle routing to delays in delivery of critical services. These problems can be addressed by (a) standards for map databases, (b) intelligent messaging, (c) national integration efforts to improve database quality in the long term. This paper examines the dimensions of the problem, and describes solutions currently under development.

Simultaneous solution and MINLP synthesis of DAE process problems: PFR networks in overall processes.

The main aim of this contribution is to describe a more general procedure for simultaneous solution and MINLP synthesis of process problems that are represented in an equation oriented modelling environment, by differential-algebraic systems of equations (DAE). An Orthogonal Collocation on Finite Elements (OCFE) has been used to discretize differential equations by some reasonable polynomial approximation and embedded into an MINLP problem formulation. In the context of the problems, three modifications are proposed. The first one concerns the problem of discontinuities caused by inequality constraints or bounds on profiles. Based on recent investigations, a more general smoothing procedure has been proposed by which it is possible to efficiently solve problems with discontinuities. Since the optimal solution is bracketed in one of the FEs, with the second modification we overcome the problem of the optimal finite element location by an appropriate MINLP formulation. Finally, the third modification concerns a reasonable simplification of the OCFE model for the production rate in PFR chemical reactor, which in this way becomes suitable for simultaneous solution and MINLP synthesis. The proposed simultaneous solution of DAE and MINLP synthesis has been tested and applied to the synthesis of the PFR reactor network in the overall HDA process scheme. It has been shown that incorrect topology can be predicted in the reactor network as well as in the whole HDA process when the modelling approximation of DAEs is too weak.

An optimized calculation of phase diagram and thermodynamic properties of the NiCr system

Optimised calculations of phase diagram (PD) and thermodynamic properties of the Ni-Cr system were carried out in [12]–[14] The incorrect topology of phase diagram was obtained in these works (the eutectic diagram with two points of the equal concentration for L/Fcc equilibrium). There are some new experimental data on the thermodynamic properties of liquid phase [10] and phase equilibriums Fcc/Bcc [11] for solid alloys of this system. A calculation of phase diagram of the Ni-Cr system with consideration of topology was carried out in [15], that provides a correct form of this diagram. But the optimized procedure of experimental data on the thermodynamic properties and phase equilibriums was not realised, and the last experimental data from [10]–[11] were not used. In this work the optimisation of the different experimental data on the thermodynamic properties (67 values) and phase equilibriums (also 67 values) from work [1] which was published in 1937 year to work [11] was conducted with using restrictions, obtained from correct topology of experimental phase diagram. The choice of models for liquid, Fec and Bcc phases was carried out among the polynomial class of models for the excess thermodynamic Gibbs potential. The autonomic programme was used for the optimised calculation and choosing of models.