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arXiv 2024年

作者： Tang, Sophia Zhang, Yinuo Chatterjee, Pranam Department of Biomedical Engineering Duke University United States Management and Technology Program University of Pennsylvania United States Center of Computational Biology Duke-NUS Medical School Singapore Department of Computer Science Duke University United States Department of Biostatistics and Bioinformatics Duke University United States

Peptide therapeutics, a major class of medicines, have achieved remarkable success across diseases such as diabetes and cancer, with landmark examples such as GLP-1 receptor agonists revolutionizing the treatment of type-2 diabetes and obesity. Despite their success, designing peptides that satisfy multiple conflicting objectives, such as target binding affinity, solubility, and membrane permeability, remains a major challenge. Classical drug development and target structure-based design are ineffective for such tasks, as they fail to optimize global functional properties critical for therapeutic efficacy. Existing generative frameworks are largely limited to continuous spaces, unconditioned outputs, or single-objective guidance, making them unsuitable for discrete sequence optimization across multiple properties. To address this, we present PepTune, a multi-objective discrete diffusion model for the simultaneous generation and optimization of therapeutic peptide SMILES. Built on the Masked Discrete Language Model (MDLM) framework, PepTune ensures valid peptide structures with bond-dependent masking schedules and penalty-based objectives. To guide the diffusion process, we propose a Monte Carlo Tree Search (MCTS)-based strategy that balances exploration and exploitation to iteratively refine Pareto-optimal sequences. MCTS integrates classifier-based rewards with search-tree expansion, overcoming gradient estimation challenges and data sparsity. Using PepTune, we generate diverse, chemically modified peptides optimized for multiple therapeutic properties, including target binding affinity, membrane permeability, solubility, hemolysis, and non-fouling for various disease-relevant targets. In total, our results demonstrate that MCTS-guided masked discrete diffusion is a powerful and modular approach for multi-objective sequence design in discrete state spaces. © 2024, CC BY-NC-ND.

关键词： Trees (mathematics)

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A software framework integrating gene expression patterns, binding site analysis and gene ontology to hypothesize gene regulation relationships

A software framework integrating gene expression patterns, b...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Pujan Joshi Baikang Pei Seung-Hyun Hong Ivo Kalajzic Dong-Ju Shin David Rowe Dong-Guk Shin Computer Science and Engineering University of Connecticut Storrs CT Computational Biology and Bioinformatics Yale University New Haven CT Genetics & Dev. Biology University of Connecticut Health Center Farmington CT Metabolic Signaling and Disease Program Sanford-Burnham Medical Research Institute Orlando FL

One known challenge in analyzing gene expression data is to combine analysis outcomes obtained disparately by applying multiple, independent meta-analysis methods. Here we present an integrative computational system that narrows down biological hypotheses by integrating gene expression patterns, transcription factor (TF) binding site analysis outcomes, and Gene Ontology (GO) enrichment analysis outcomes. This system identifies regulated genes from microarray experiments through statistical processes, categorizes similarly behaving groups of genes and then carries out binding site analysis and gene function enrichment analysis based on some significant clusters. The output is an ordered set of "putative" pair-wise relationships between TFs and their potential target genes. The relationships are ranked based on their closeness to the experimental context. We demonstrate the effectiveness of our framework using two independent microarray data sets.

关键词： Gene expression Context Sociology Statistics Bioinformatics Bones

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Representing and extending ensembles of parsimonious evolutionary histories with a directed acyclic graph

arXiv

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arXiv 2023年

作者： Dumm, Will Barker, Mary Howard-Snyder, William DeWitt, William S. Matsen, Frederick A. Computational Biology Program Fred Hutchinson Cancer Research Center SeattleWA United States Howard Hughes Medical Institute Computational Biology Program Fred Hutchinson Cancer Research Center SeattleWA United States Paul G. Allen School of Computer Science and Engineering University of Washington SeattleWA United States Department of Electrical Engineering and Computer Sciences University of California BerkeleyCA United States Department of Genome Sciences University of Washington SeattleWA United States Department of Statistics University of Washington SeattleWA United States

In many situations, it would be useful to know not just the best phylogenetic tree for a given data set, but the collection of high-quality trees. This goal is typically addressed using Bayesian techniques, however, current Bayesian methods do not scale to large data sets. Furthermore, for large data sets with relatively low signal one cannot even store every good tree individually, especially when the trees are required to be bifurcating. In this paper, we develop a novel object called the "history subpartition directed acyclic graph" (or "history sDAG" for short) that compactly represents an ensemble of trees with labels (e.g. ancestral sequences) mapped onto the internal nodes. The history sDAG can be built efficiently and can also be efficiently trimmed to only represent maximally parsimonious trees. We show that the history sDAG allows us to find many additional equally parsimonious trees, extending combinatorially beyond the ensemble used to construct it. We argue that this object could be useful as the "skeleton" of a more complete uncertainty *** Codes 92-08 (Primary) 92B10, 92-04 (Secondary) Copyright © 2023, The Authors. All rights reserved.

关键词： Phylogenetic

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Global variations in critical drought thresholds that impact vegetation

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National science Review 2023年第5期10卷 180-193页

作者： Xiangyi Li Shilong Piao Chris Huntingford Josep Pe?uelas Hui Yang Hao Xu Anping Chen Pierre Friedlingstein Trevor F.Keenan Stephen Sitch Xuhui Wang Jakob Zscheischler Miguel D.Mahecha Sino-French Institute for Earth System Science College of Urban and Environmental SciencesPeking University Key Laboratory of Alpine Ecology and Biodiversity Institute of Tibetan Plateau ResearchCenter for Excellence in Tibetan Earth ScienceChinese Academy of Sciences UK Centre for Ecology and Hydrology CSIC Global Ecology Unit CREAF-CSIC-UAB CREAF Cerdanyola de Vallès Department of Biogeochemical Integration Max Planck Institute for Biogeochemistry Department of Biology Colorado State University Graduate Degree Program in Ecology Colorado State University Department of Mathematics College of Engineering Mathematics and Physical SciencesUniversity of Exeter Laboratoire de Météorologie Dynamique Institut Pierre-Simon LaplaceCNRS-ENS-UPMC-XDépartement de GeósciencesEcole Normale Superieure Earth and Environmental Sciences Area Lawrence Berkeley National Laboratory Department of Environmental Science Policy&ManagementUniversity of California Berkeley Department of Geography College of Life and Environmental SciencesUniversity of Exeter Department of Computational Hydrosystems Helmholtz Centre for Environmental Research—Ufz Remote Sensing Centre for Earth System Research Leipzig University

Identifying the thresholds of drought that,if crossed,suppress vegetation functioning is vital for accurate quantification of how land ecosystems respond to climate variability and *** present a globally applicable framework to identify drought thresholds for vegetation responses to different levels of known soil-moisture deficits using four remotely sensed vegetation proxies spanning *** thresholds identified represent critical inflection points for changing vegetation responses from highly resistant to highly vulnerable in response to drought stress,and as a warning signal for substantial vegetation *** thresholds varied geographically,with much lower percentiles of soil-moisture anomalies in vegetated areas covered by more forests,corresponding to a comparably stronger capacity to mitigate soil water deficit stress in forested ***,those lower thresholds are detected in more humid ***-of-the-art land models,however,overestimated thresholds of soil moisture(*** drought impacts),especially in more humid areas with higher forest covers and arid areas with few forest *** on climate model projections,we predict that the risk of vegetation damage will increase by the end of the twenty-first century in some hotspots like East Asia,Europe,Amazon,southern Australia and eastern and southern *** data-based results will inform projections on future drought impacts on terrestrial ecosystems and provide an effective tool for drought management.

关键词： drought threshold inflection points vegetation response soil moisture drought impacts

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A General Iterative Procedure of the Non-Numerical Ranking Preferences Method for Multiple Objective Decision Making

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Procedia Computer science 2012年 12卷 135-139页

作者： Victor M. Carrillo Heidi Taboada Computational Science Program. The University of Texas at El Paso 500 West University Av El Paso TX 79968-0521 United States of America Department of Industrial Manufacturing and Systems Engineering. The University of Texas at El Paso 500 West University Av El Paso TX 79968-0521 United States of America

Multiple objective evolutionary algorithms (MOEAs), which are biologically-inspired optimization methods, have become popular approaches to solve problems with multiple objective functions. With the use of MOEAs, multiple objective optimization becomes a two-part problem. First, the multiple objective optimization problem needs to be formulated and successfully solved using an MOEA. Then, a non- dominated set -also known as efficient or Pareto frontier- needs to be analyzed to select a solution to the problem. This can represent a challenging task to the decision-maker because this set can contain a large number of solutions. This decision- making stage is usually known as the post-Pareto analysis stage. This paper presents the generalization of a post-Pareto optimality method known as the non-numerical ranking preferences (NNRP) method originally proposed by Taboada et al . (2007). This method can help decision makers reduce the number of design possibilities to small subsets that clearly reflect their objective function preferences. Previous research has only presented the application of the NNRP method using three and four objective functions but had not been generalized to the case of n objective functions. The present paper expands the NNRP method to be able to consider multiple objective optimization problems with n number of objective functions.

关键词： post-Pareto optimality decision making multi-objective optimization

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Novel Low-Temperature Behavior in Classical Many-Particle Systems

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Physical Review Letters 2009年第5期103卷 050602-050602页

作者： Robert D. Batten Frank H. Stillinger Salvatore Torquato Department of Chemical Engineering Princeton University Princeton New Jersey 08544 USA Department of Chemistry Princeton University Princeton New Jersey 08544 USA Princeton Materials Institute Program in Applied and Computational Mathematics Princeton Center for Theoretical Science Princeton University Princeton New Jersey 08544 USA School of Natural Sciences Institute for Advanced Study Princeton New Jersey 08544 USA

We show that classical many-particle systems interacting with certain soft pair interactions in two dimensions exhibit novel low-temperature behaviors. Ground states span from disordered to crystalline. At some densities, a large fraction of normal-mode frequencies vanish. Lattice ground-state configurations have more vanishing frequencies than disordered ground states at the same density and exhibit vanishing shear moduli. For the melting transition from a crystal, the thermal expansion coefficient is negative. These unusual results are attributed to the topography of the energy landscape.

关键词： Ground state

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Effects of concurrency on epidemic spreading in Markovian temporal networks

arXiv

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arXiv 2022年

作者： Liu, Ruodan Ogura, Masaki Reis, Elohim Fonseca Dos Masuda, Naoki Department of Mathematics State University of New York at Buffalo BuffaloNY14260-2900 United States Graduate School of Information Science and Technology Osaka University Osaka Suita565-0871 Japan Computational and Data-Enabled Sciences and Engineering Program State University of New York at Buffalo BuffaloNY14260-5030 United States Faculty of Science and Engineering Waseda University Tokyo169-8555 Japan

The concurrency of edges, quantified by the number of edges that share a common node at a given time point, may be an important determinant of epidemic processes in temporal networks. We propose theoretically tractable Markovian temporal network models in which each edge flips between the active and inactive states in continuous time. The different models have different amounts of concurrency while we can tune the models to share the same statistics of edge activation and deactivation (and hence the fraction of time for which each edge is active) and the structure of the aggregate (i.e., static) network. We analytically calculate the amount of concurrency of edges sharing a node for each model. We then numerically study effects of concurrency on epidemic spreading in the stochastic susceptible-infectious-susceptible and susceptible-infectious-recovered dynamics on the proposed temporal network models. We find that the concurrency enhances epidemic spreading near the epidemic threshold while this effect is small in many cases. Furthermore, when the infection rate is substantially larger than the epidemic threshold, the concurrency suppresses epidemic spreading in a majority of cases. In sum, our numerical simulations suggest that the impact of concurrency on enhancing epidemic spreading within our model is consistently present near the epidemic threshold but modest. The proposed temporal network models are expected to be useful for investigating effects of concurrency on various collective dynamics on networks including both infectious and other dynamics. Copyright © 2022, The Authors. All rights reserved.

关键词： Dynamics

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Invasive or More Direct Measurements Can Provide an Objective Early-Stopping Ceiling for Training Deep Neural Networks on Non-invasive or Less-Direct Biomedical Data

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SN Computer science 2023年第2期4卷 161页

作者： Bartlett, Christopher W. Bossenbroek, Jamie Ueyama, Yukie McCallinhart, Patricia Peters, Olivia A. Santillan, Donna A. Santillan, Mark K. Trask, Aaron J. Ray, William C. Department of Pediatrics The Ohio State University College of Medicine Columbus OH United States The Steve and Cindy Rasmussen Institute for Genomic Medicine Battelle Center for Computational Biology The Abigail Wexner Research Institute at Nationwide Children’s Hospital Columbus OH United States Department of Computer Science and Engineering The Ohio State University College of Engineering Columbus OH United States Center for Cardiovascular Research The Abigail Wexner Research Institute at Nationwide Children’s Hospital Columbus OH United States Department of Obstetrics & Gynecology University of Iowa Hospitals & Clinics Iowa City IA United States The Interdisciplinary Graduate Program in Biophysics The Ohio State University Graduate School Columbus OH United States

Early stopping is an extremely common tool to minimize overfitting, which would otherwise be a cause of poor generalization of the model to novel data. However, early stopping is a heuristic that, while effective, primarily relies on ad hoc parameters and metrics. Optimizing when to stop remains a challenge. In this paper, we suggest that for some biomedical applications, a natural dichotomy of invasive/non-invasive measurements, or more generally proximal vs distal measurements of a biological system can be exploited to provide objective advice on early stopping. We discuss the conditions where invasive measurements of a biological process should provide better predictions than non-invasive measurements, or at best offer parity. Hence, if data from an invasive measurement are available locally, or from the literature, that information can be leveraged to know with high certainty whether a model of non-invasive data is overfitted. We present paired invasive/non-invasive cardiac and coronary artery measurements from two mouse strains, one of which spontaneously develops type 2 diabetes, posed as a classification problem. Examination of the various stopping rules shows that generalization is reduced with more training epochs and commonly applied stopping rules give widely different generalization error estimates. The use of an empirically derived training ceiling is demonstrated to be helpful as added information to leverage early stopping in order to reduce overfitting. © 2023, The Author(s).

关键词： Health Invasive Machine learning Model Non-invasive Overfitting

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MultiCalib4DEB: A toolbox exploiting multimodal optimisation in Dynamic Energy Budget parameters calibration

arXiv

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arXiv 2023年

作者： Robles, Juan Francisco Chica, Manuel Filgueira, Ramón Agüera, Antonio Damas, Sergio Department of Computer Science and Artificial Intelligence Andalusian Research Institute in Data Science and Computational Intelligence DaSCI University of Granada Granada18071 Spain Department of Benthic resources Norwegian Institute of Marine Research BergenNO-5817 Norway Department of Software Engineering Andalusian Research Institute in Data Science and Computational Intelligence DaSCI University of Granada Granada18071 Spain Marine Affairs Program Life Sciences Centre Dalhousie University 1459 Oxford Street HalifaxNSB3H 4R2 Canada

1. Calibration is a crucial step for the validation of computational models and a challenging task to accomplish. 2. Dynamic Energy Budget (DEB) theory has experienced an exponential rise in the number of published papers, which in large part has been made possible by the DEBtool toolbox. Multimodal evolutionary optimisation could provide DEBtool with new capabilities, particularly relevant on the provisioning of equally optimal and diverse solutions. 3. In this paper we present MultiCalib4DEB, a MATLAB toolbox directly integrated into the existing DEBtool toolbox, which uses multimodal evolutionary optimisation algorithms to find multiple global and local optimal and diverse calibration solutions for DEB models. 4. MultiCalib4DEB adds powerful calibration mechanisms, statistical analysis, and visualisation methods to the DEBtool toolbox and provides a wide range of outputs, different calibration alternatives, and specific tools to strengthen the DEBtool calibration module and to aid DEBtool users to evaluate the performance of the calibration results. © 2023, CC BY-NC-ND.

关键词： Calibration

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The Waiting-Time Paradox

arXiv

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arXiv 2020年

作者： Masuda, Naoki Porter, Mason A. Department of Mathematics State University of New York at Buffalo BuffaloNY United States Computational and Data-Enabled Science and Engineering Program State University of New York at Buffalo BuffaloNY United States Department of Mathematics University of California Los Angeles Los AngelesCA United States

Suppose that you’re going to school and arrive at a bus stop. How long do you have to wait before the next bus arrives? Surprisingly, it is longer — possibly much longer — than what the bus schedule suggests intuitively. This phenomenon, called the waiting-time paradox, has a purely mathematical origin. Different buses arrive with different intervals, leading to this paradox. In this article, we look at the waiting-time paradox, explain why it happens, and explore some of its implications (beyond the possibility of being late for school). Copyright © 2020, The Authors. All rights reserved.

关键词： Buses

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