pwc-archive/papers-with-abstracts huggingface dataset:
Identifying 3D Genome Organization in Diploid Organisms via Euclidean Distance Geometry
Authors: Anastasiya Belyaeva, Kaie Kubjas, Lawrence J. Sun, Caroline Uhler
Date: 2021-01-13 00:00:00

The spatial organization of the DNA in the cell nucleus plays an important role for gene regulation, DNA replication, and genomic integrity. Through the development of chromosome conformation capture experiments (such as 3C, 4C, Hi-C) it is now possible to obtain the contact frequencies of the DNA at the whole-genome level. In this paper, we study the problem of reconstructing the 3D organization of the genome from such whole-genome contact frequencies. A standard approach is to transform the contact frequencies into noisy distance measurements and then apply semidefinite programming (SDP) formulations to obtain the 3D configuration. However, neglected in such reconstructions is the fact that most eukaryotes including humans are diploid and therefore contain two copies of each genomic locus. We prove that the 3D organization of the DNA is not identifiable from distance measurements derived from contact frequencies in diploid organisms. In fact, there are infinitely many solutions even in the noise-free setting. We then discuss various additional biologically relevant and experimentally measurable constraints (including distances between neighboring genomic loci and higher-order interactions) and prove identifiability under these conditions. Furthermore, we provide SDP formulations for computing the 3D embedding of the DNA with these additional constraints and show that we can recover the true 3D embedding with high accuracy from both noiseless and noisy measurements. Finally, we apply our algorithm to real pairwise and higher-order contact frequency data and show that we can recover known genome organization patterns.
Replicating Market Makers
Authors: Guillermo Angeris, Alex Evans, Tarun Chitra
Date: 2021-03-26 00:00:00

We present a method for constructing Constant Function Market Makers (CFMMs) whose portfolio value functions match a desired payoff. More specifically, we show that the space of concave, nonnegative, nondecreasing, 1-homogeneous payoff functions and the space of convex CFMMs are equivalent; in other words, every CFMM has a concave, nonnegative, nondecreasing, 1-homogeneous payoff function, and every payoff function with these properties has a corresponding convex CFMM. We demonstrate a simple method for recovering a CFMM trading function that produces this desired payoff. This method uses only basic tools from convex analysis and is intimately related to Fenchel conjugacy. We demonstrate our result by constructing trading functions corresponding to basic payoffs, as well as standard financial derivatives such as options and swaps.
Robust Portfolio Selection Problems: A Comprehensive Review
Authors: Alireza Ghahtarani, Ahmed Saif, Alireza Ghasemi
Date: 2021-03-23 00:00:00

In this paper, we provide a comprehensive review of recent advances in robust portfolio selection problems and their extensions, from both operational research and financial perspectives. A multi-dimensional classification of the models and methods proposed in the literature is presented, based on the types of financial problems, uncertainty sets, robust optimization approaches, and mathematical formulations. Several open questions and potential future research directions are identified.
Monte Carlo algorithm for the extrema of tempered stable processes
Authors: Jorge Ignacio González Cázares, Aleksandar Mijatović
Date: 2021-03-29 00:00:00

We develop a novel Monte Carlo algorithm for the vector consisting of the supremum, the time at which the supremum is attained and the position at a given (constant) time of an exponentially tempered L\'evy process. The algorithm, based on the increments of the process without tempering, converges geometrically fast (as a function of the computational cost) for discontinuous and locally Lipschitz functions of the vector. We prove that the corresponding multilevel Monte Carlo estimator has optimal computational complexity (i.e. of order $\varepsilon^{-2}$ if the mean squared error is at most $\varepsilon^2$) and provide its central limit theorem (CLT). Using the CLT we construct confidence intervals for barrier option prices and various risk measures based on drawdown under the tempered stable (CGMY) model calibrated/estimated on real-world data. We provide non-asymptotic and asymptotic comparisons of our algorithm with existing approximations, leading to rule-of-thumb guidelines for users to the best method for a given set of parameters. We illustrate the performance of the algorithm with numerical examples.
A Quantum algorithm for linear PDEs arising in Finance
Authors: Filipe Fontanela, Antoine Jacquier, Mugad Oumgari
Date: 2019-12-05 00:00:00

We propose a hybrid quantum-classical algorithm, originated from quantum chemistry, to price European and Asian options in the Black-Scholes model. Our approach is based on the equivalence between the pricing partial differential equation and the Schrodinger equation in imaginary time. We devise a strategy to build a shallow quantum circuit approximation to this equation, only requiring few qubits. This constitutes a promising candidate for the application of Quantum Computing techniques (with large number of qubits affected by noise) in Quantitative Finance.
Instance-Dependent Bounds for Zeroth-order Lipschitz Optimization with Error Certificates
Authors: François Bachoc, Tommaso R Cesari, Sébastien Gerchinovitz
Date: 2021-02-03 00:00:00
Proceeding: NeurIPS 2021 12

We study the problem of zeroth-order (black-box) optimization of a Lipschitz function $f$ defined on a compact subset $\mathcal X$ of $\mathbb R^d$, with the additional constraint that algorithms must certify the accuracy of their recommendations. We characterize the optimal number of evaluations of any Lipschitz function $f$ to find and certify an approximate maximizer of $f$ at accuracy $\varepsilon$. Under a weak assumption on $\mathcal X$, this optimal sample complexity is shown to be nearly proportional to the integral $\int_{\mathcal X} \mathrm{d}\boldsymbol x/( \max(f) - f(\boldsymbol x) + \varepsilon )^d$. This result, which was only (and partially) known in dimension $d=1$, solves an open problem dating back to 1991. In terms of techniques, our upper bound relies on a packing bound by Bouttier al. (2020) for the Piyavskii-Shubert algorithm that we link to the above integral. We also show that a certified version of the computationally tractable DOO algorithm matches these packing and integral bounds. Our instance-dependent lower bound differs from traditional worst-case lower bounds in the Lipschitz setting and relies on a local worst-case analysis that could likely prove useful for other learning tasks.
Multivariate tail covariance for generalized skew-elliptical distributions
Authors: Baishuai Zuo, Chuancun Yin
Date: 2021-03-09 00:00:00

In this paper, the multivariate tail covariance (MTCov) for generalized skew-elliptical distributions is considered. Some special cases for this distribution, such as generalized skew-normal, generalized skew student-t, generalized skew-logistic and generalized skew-Laplace distributions, are also considered. In order to test the theoretical feasibility of our results, the MTCov for skewed and non skewed normal distributions are computed and compared. Finally, we give a special formula of the MTCov for generalized skew-elliptical distributions.
ViralFP: A webserver of viral fusion proteins
Authors: Pedro Moreira, Ana Marta Sequeira, Sara Pereira, Rúben Rodrigues, Miguel Rocha, Diana Lousa
Date: 2021-03-26 00:00:00

Viral fusion proteins are attached to the membrane of enveloped viruses (a group that includes Coronaviruses, Dengue, HIV and Influenza) and catalyze fusion between the viral and host membranes, enabling the virus to insert its genetic material into the host cell. Given the importance of these biomolecules, this work presents a centralized database containing the most relevant information on viral fusion proteins, available through a free-to-use web server accessible through the URL https://viralfp.bio.di.uminho.pt/. This web application contains several bioinformatic tools, such as Clustal sequence alignment and Weblogo, including as well a machine learning-based tool capable of predicting the location of fusion peptides (the component of fusion proteins that inserts into the host's cell membrane) within the fusion protein sequence. Given the crucial role of these proteins in viral infection, their importance as natural targets of our immune system and their potential as therapeutic targets, this web application aims to foster our ability to fight pathogenic viruses.
Liquid-liquid phase separation, biomolecular condensates, puncta, non-stoichiometric supramolecular assemblies, membraneless organelles, and bacterial chemotaxis are best understood as emergent phenomena with switch-like behaviour
Authors: Richard P Sear
Date: 2021-03-15 00:00:00

Liquid-liquid phase separation (LLPS) is currently of great interest in cell biology. LLPS is an example of what is called an emergent phenomenon -- an idea that comes from condensed-matter physics. Emergent phenomena have the characteristic feature of having a switch-like response. I show that the Hill equation of biochemistry can be used as a simple model of strongly cooperative, switch-like, behaviour. One result is that a switch-like response requires relatively few molecules, even ten gives a strongly switch-like response. Thus if a biological function enabled by LLPS relies on LLPS to provide a switch-like response to a stimulus, then condensates large enough to be visible in optical microscopy are not needed.
Three-fold mechanism of inhibition of SARS-CoV-2 infection by the interaction of the spike glycoprotein with heparin
Authors: Giulia Paiardi, Stefan Richter, Pasqua Oreste, Chiara Urbinati, Marco Rusnati, Rebecca C. Wade
Date: 2021-03-13 00:00:00

Heparin has been found to have antiviral activity against SARS-CoV-2. Here, by means of sliding window docking, molecular dynamics simulations and biochemical assays, we investigate the binding mode of heparin to the virus spike glycoprotein and the molecular basis for its antiviral activity. The simulations show that heparin binds at long, mostly positively charged patches on the spike, thereby masking the basic residues of the receptor binding domain and of the S1/S2 site. Experiments corroborated the simulation results by showing that heparin inhibits the cleavage of spike by furin by binding to the basic S1/S2 site. Our results indicate that heparin exerts its antiviral activity by both direct and allosteric mechanisms. Furthermore, the simulations provide insights into how heparan sulfate proteoglycans on the host cell can facilitate viral infection. Our results will aid the rational optimization of heparin derivatives for SARS-CoV-2 antiviral therapy.
Information-Driven Modeling of Biomolecular Complexes
Authors: Charlotte W. van Noort, Rodrigo V. Honorato, Alexandre M. J. J. Bonvin
Date: 2021-03-12 00:00:00
Tasks: Molecular Docking

Proteins play crucial roles in every cellular process by interacting with each other, with nucleic acids, metabolites, and other molecules. The resulting assemblies can be very large and intricate and pose challenges to experimental methods. In the current era of integrative modeling, it is often only by a combination of various experimental techniques and computations that 3D models of those molecular machines can be obtained. Among the various computational approaches available, molecular docking is often the method of choice when it comes to predicting 3D structures of complexes. Docking can generate particularly accurate models when taking into account the available information on the complex of interest. We review here the use of experimental and bioinformatics data in protein-protein docking, describing recent software developments and highlighting applications for the modeling of antibody-antigen complexes and membrane protein complexes, and the use of evolutionary and shape information.
Thoughts on the Proteins Native State
Authors: Jorge A. Vila
Date: 2021-02-26 00:00:00

The presence of metamorphism in the protein's native state is not yet fully understood. In an attempt to throw light on this issue here we present an assessment, in terms of the amide hydrogen exchange protection factor, that aims to determine the likely existence of structural fluctuations in the native-state consistent with both the upper bound marginal stability of proteins and the metamorphism presence. The preliminary results enable us to conclude that the native-state metamorphism is, indeed, more probable than thought.
Hydrophobic interaction determines docking affinity of SARS CoV 2 variants with antibodies
Authors: Jiacheng Li, Chengyu Hou, Menghao Wang, Chencheng Liao, Shuai Guo, Liping Shi, Xiaoliang Ma, Hongchi Zhang, Shenda Jiang, Bing Zheng, Lin Ye, Lin Yang, Xiaodong He
Date: 2021-02-28 00:00:00

Preliminary epidemiologic, phylogenetic and clinical findings suggest that several novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants have increased transmissibility and decreased efficacy of several existing vaccines. Four mutations in the receptor-binding domain (RBD) of the spike protein that are reported to contribute to increased transmission. Understanding physical mechanism responsible for the affinity enhancement between the SARS-CoV-2 variants and ACE2 is the "urgent challenge" for developing blockers, vaccines and therapeutic antibodies against the coronavirus disease 2019 (COVID-19) pandemic. Based on a hydrophobic-interaction-based protein docking mechanism, this study reveals that the mutation N501Y obviously increased the hydrophobic attraction and decrease hydrophilic repulsion between the RBD and ACE2 that most likely caused the transmissibility increment of the variants. By analyzing the mutation-induced hydrophobic surface changes in the attraction and repulsion at the binding site of the complexes of the SARS-CoV-2 variants and antibodies, we found out that all the mutations of N501Y, E484K, K417N and L452R can selectively decrease or increase their binding affinity with some antibodies.
Persistent topology of protein space
Authors: W. Hamilton, J. E. Borgert, T. Hamelryck, J. S. Marron
Date: 2021-02-12 00:00:00

Protein fold classification is a classic problem in structural biology and bioinformatics. We approach this problem using persistent homology. In particular, we use alpha shape filtrations to compare a topological representation of the data with a different representation that makes use of knot-theoretic ideas. We use the statistical method of Angle-based Joint and Individual Variation Explained (AJIVE) to understand similarities and differences between these representations.
A Simple Explicit-Solvent Model of Polyampholyte Phase Behaviors and its Ramifications for Dielectric Effects in Biomolecular Condensates
Authors: Jonas Wessén, Tanmoy Pal, Suman Das, Yi-Hsuan Lin, Hue Sun Chan
Date: 2021-02-06 00:00:00
Tasks: Dielectric Constant

Biomolecular condensates such as membraneless organelles, underpinned by liquid-liquid phase separation (LLPS), are important for physiological function, with electrostatics -- among other interaction types -- being a prominent force in their assembly. Charge interactions of intrinsically disordered proteins (IDPs) and other biomolecules are sensitive to the aqueous dielectric environment. Because the relative permittivity of protein is significantly lower than that of water, the interior of an IDP condensate is a relatively low-dielectric regime, which, aside from its possible functional effects on client molecules, should facilitate stronger electrostatic interactions among the scaffold IDPs. To gain insight into this LLPS-induced dielectric heterogeneity, addressing in particular whether a low-dielectric condensed phase entails more favorable LLPS than that posited by assuming IDP electrostatic interactions are uniformly modulated by the higher dielectric constant of the pure solvent, we consider a simplified multiple-chain model of polyampholytes immersed in explicit solvents that are either polarizable or possess a permanent dipole. Notably, simulated phase behaviors of these systems exhibit only minor to moderate differences from those obtained using implicit-solvent models with a uniform relative permittivity equals to that of pure solvent. Buttressed by theoretical treatments developed here using random phase approximation and polymer field-theoretic simulations, these observations indicate a partial compensation of effects between favorable solvent-mediated interactions among the polyampholytes in the condensed phase and favorable polyampholyte-solvent interactions in the dilute phase, often netting only a minor enhancement of overall LLPS propensity from the very dielectric heterogeneity that arises from the LLPS itself. Further ramifications of this principle are discussed.
Conformational Biases of α-Synuclein and Formation of Transient Knots
Authors: Mateusz Chwastyk, Marek Cieplak
Date: 2021-02-06 00:00:00

We study local conformational biases in the dynamics of {\alpha}-synuclein by using all-atom simulations with explicit and implicit solvents. The biases are related to the frequency of the specific contact formation. In both approaches, the protein is intrinsically disordered, and its strongest bias is to make bend and turn local structures. The explicit-solvent conformations can be substantially more extended which allows for formation of transient trefoil knots, both deep and shallow, that may last for up to 5 {\mu}s. The two-chain self-association events, both short- and long-lived, are dominated by formation of contacts in the central part of the sequence. This part tends to form helices when bound to a micelle.
A Novel Antimicrobial Electrochemical Glucose Biosensor Based on Silver-Prussian Blue Modified TiO$_2$ Nanotube Arrays
Authors: Nasim Farajpour, Ram Deivanayagam, Abhijit Phakatkar, Surya Narayanan, Reza Shahbazian-Yassar, Tolou Shokuhfar
Date: 2021-01-31 00:00:00
Tasks: Sensitivity

Glucose biosensors play an important role in the diagnosis and continued monitoring of the disease, diabetes mellitus. This report proposes the development of a novel enzymatic electrochemical glucose biosensor based on TiO$_2$ nanotubes modified by AgO and Prussian blue (PB) nanoparticles (NPs), which has an additional advantage of possessing antimicrobial properties for implantable biosensor applications. In this study, we developed two high performance glucose biosensors based on the immobilization of glucose oxidase (GOx) onto Prussian blue (PB) modified TiO$_2$ nanotube arrays functionalized by Au and AgO NPs. AgO-deposited TiO$_2$ nanotubes were synthesized through an electrochemical anodization process followed by Ag electroplating process in the same electrolyte. Deposition of PB particles was performed from an acidic ferricyanide solution. The surface morphology and elemental composition of the two fabricated biosensors were investigated by scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS) which indicate the successful deposition of Au and AgO nanoparticles as well as PB nanocrystals. Cyclic voltammetry and chronoamperometry were used to investigate the performance of the modified electrochemical biosensors. The results show that the developed electrochemical biosensors display excellent properties in terms of electron transmission, low detection limit as well as high stability for the determination of glucose. Under the optimized conditions, the amperometric response shows a linear dependence on the glucose concentration to a detection limit down to 4.91 $\mu$M with sensitivity of 185.1 mA M$^{-1}$ cm$^{-2]$ in Au modified biosensor and detection limit of 58.7 $\mu$M with 29.1 mA M$^{-1}$ cm$^{-2]$ sensitivity in AgO modified biosensor.
essHi-C: Essential component analysis of Hi-C matrices
Authors: Stefano Franzini, Marco Di Stefano, Cristian Micheletti
Date: 2021-01-26 00:00:00
Tasks: Clustering

Motivation: Hi-C matrices are cornerstones for qualitative and quantitative studies of genome folding, from its territorial organization to compartments and topological domains. The high dynamic range of genomic distances probed in Hi-C assays reflects in an inherent stochastic background of the interactions matrices, which inevitably convolve the features of interest with largely aspecific ones. Results: Here we introduce a discuss essHi-C, a method to isolate the specific, or essential component of Hi-C matrices from the aspecific portion of the spectrum that is compatible with random matrices. Systematic comparisons show that essHi-C improves the clarity of the interaction patterns, enhances the robustness against sequencing depth, allows the unsupervised clustering of experiments in different cell lines and recovers the cell-cycle phasing of single-cells based on Hi-C data. Thus, essHi-C provides means for isolating significant biological and physical features from Hi-C matrices.
Regulation by Progestins, Corticosteroids and RU486 of Activation of Elephant Shark and Human Progesterone Receptors: An Evolutionary Perspec
Authors: Xiaozhi Lin, Wataru Takagi, Susumu Hyodo, Shigeho Ijiri, Yoshinao Katsu, Michael E. Baker
Date: 2021-01-24 00:00:00
Tasks: Specificity

We investigated progestin and corticosteroid activation of the progesterone receptor (PR) from elephant shark (Callorhinchus milii), a cartilaginous fish belonging to the oldest group of jawed vertebrates. Comparison with human PR experiments provides insights into the evolution of steroid activation of human PR. At 1 nM steroid, elephant shark PR is activated by progesterone, 17-hydroxy-progesterone, 20beta-hydroxy-progesterone, 11-deoxycorticosterone (21-hydroxyprogesterone) and 11-deoxycortisol. At 1 nM steroid, human PR is activated only by progesterone and11-deoxycorticosterone indicating increased specificity for progestins and corticosteroids during the evolution of human PR. RU486, an important clinical antagonist of human PR, did not inhibit progesterone activation of elephant shark PR. Cys-528 in elephant shark PR corresponds to Gly-722 in human PR, which is essential for RU486 inhibition of human PR. Confirming the importance of this site on elephant shark PR, RU486 inhibited progesterone activation of the Cys528Gly mutant PR. There also was a decline in activation of elephant shark Cys528Gly PR by 11-deoxycortisol, 17-hydroxy-progesterone and 20beta-hydroxy-progesterone and an increase in activation of human Gly722Cys PR by 11-deoxycortisol and decreased activation by corticosterone. One or more of these changes may have selected for the mutation corresponding to human glycine-722 PR that first evolved in platypus PR, a basal mammal.
A quantitative model for a nanoscale switch accurately predicts thermal actuation behavior
Authors: Kyle Crocker, Joshua Johnson, Wolfgang Pfeifer, Carlos Castro, Ralf Bundschuh
Date: 2021-01-20 00:00:00

Manipulation of temperature can be used to actuate DNA origami nano-hinges containing gold nanoparticles. We develop a physical model of this system that uses partition function analysis of the interaction between the nano-hinge and nanoparticle to predict the probability that the nano-hinge is open at a given temperature. The model agrees well with experimental data and predicts experimental conditions that allow the actuation temperature of the nano-hinge to be tuned over a range of temperatures from $30$${}^{\circ}\mathrm{C}$ to $45$${}^{\circ}\mathrm{C}$. Additionally, the model reveals surprising physical constraints on the system. This combination of physical insight and predictive potential is likely to inform future designs that integrate nanoparticles into dynamic DNA origami structures. Furthermore, our modeling approach could be expanded to consider the incorporation, stability, and actuation of other types of functional elements or actuation mechanisms integrated into nucleic acid devices.