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BIOCELL 2023年第6期47卷 1225-1241页

作者： MIRKO TRECCANI ELENA LOCATELLI CRISTINA PATUZZO GIOVANNI MALERBA GMLab Department of NeurosciencesBiomedicine and Movement SciencesUniversity of VeronaVerona37134Italy

The advent of genomic big data and the statistical need for reaching significant results have led genome-wide association studies to be ravenous of a huge number of genetic markers scattered along the whole genome.Since its very beginning,the so-called genotype imputation served this purpose;this statistical and inferential procedure based on a known reference panel opened the theoretical possibility to extend association analyses to a greater number of polymorphic sites which have not been previously assayed by the used technology.In this review,we present a broad overview of the genotype imputation process,showing the most known methods and presenting the main areas of interest,with a closer look to the most up-to-date approaches and a deeper understanding of its usage in the presentday genomic landscape,shedding a light on its future developments and investigation areas.

关键词： Haplotypes Variant Calling inference Linkage Analysis NGS

Bayesian inference for dynamical systems

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Infectious Disease Modelling 2020年第1期5卷 221-232页

作者： Weston C.Roda Department of Mathematical and Statistical Sciences University of AlbertaEdmontonAB T6G 2G1Canada

Bayesian inference is a common method for conducting parameter estimation for dynamical systems.Despite the prevalent use of Bayesian inference for performing parameter estimation for dynamical systems,there is a need for a formalized and detailed methodology.This paper presents a comprehensive methodology for dynamical system parameter estimation using Bayesian inference and it covers utilizing different distributions,Markov Chain Monte Carlo(MCMC)sampling,obtaining credible intervals for parameters,and prediction intervals for solutions.A logistic growth example is given to illustrate the methodology.

关键词： Bayesian inference Model fitting Data Dynamical system Mathematical model

The Exact inference of Beta Process and Beta Bernoulli Process From Finite Observations

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Computer Modeling in Engineering & Sciences 2019年第10期121卷 49-82页

作者： Yang Cheng Dehua Li Wenbin Jiang School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan430074China School of Computer Science and Technology Huazhong University of Science and TechnologyWuhan430074China.

Beta Process is a typical nonparametric Bayesian model.and the Beta Bernoulli Process provides a Bayesian nonparametric prior for models involving collections of binary valued features.Some previous studies considered the Beta Process inference problem by giving the Stick-Breaking sampling method.This paper focuses on analyzing the form of precise probability distribution based on a Stick-Breaking approach,that is,the joint probability distribution is derived from any finite number of observable samples:It not only determines the probability distribution function of the Beta Process with finite observation(represented as a group of number between[0,1]),but also gives the distribution function of the Beta Bernoulli Process with the same finite dimension(represented as a matrix with element value of 0 or,1)by using this distribution as a prior.

关键词： Beta process joint distribution beta Bernoulli process exact inference

A selective view of stochastic inference and mod-eling problems in nanoscale biophysics

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Science China Mathematics 2009年第6期52卷 1181-1211页

作者： KOU S.C. Department of Statistics Harvard UniversityCambridgeMA 02138USA

Advances in nanotechnology enable scientists for the first time to study biological pro-cesses on a nanoscale molecule-by-molecule basis.They also raise challenges and opportunities for statisticians and applied probabilists.To exemplify the stochastic inference and modeling problems in the field,this paper discusses a few selected cases,ranging from likelihood inference,Bayesian data augmentation,and semi-and non-parametric inference of nanometric biochemical systems to the uti-lization of stochastic integro-differential equations and stochastic networks to model single-molecule biophysical processes.We discuss the statistical and probabilistic issues as well as the biophysical motivation and physical meaning behind the problems,emphasizing the analysis and modeling of real experimental data.

关键词： likelihood analysis Bayesian data augmentation semi-and non-parametric inference single-molecule experiment subdiffusion generalized Langevin equation fractional Brownian motion stochastic network enzymatic reaction

Optimizing deep learning inference on mobile devices with neural network accelerators

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High Technology Letters 2019年第4期25卷 417-425页

作者：曾惜 Xu Yunlong Zhi Tian Intelligent Processor Research Center Institute of Computing TechnologyChinese Academy of SciencesBeijing 100190P.R.China University of Chinese Academy of Sciences Beijing 100049P.R.China Cambricon Technologies Corporation Limited Beijing 100191P.R.China

Deep learning has now been widely used in intelligent apps of mobile devices.In pursuit of ultra-low power and latency,integrating neural network accelerators(NNA)to mobile phones has become a trend.However,conventional deep learning programming frameworks are not well-developed to support such devices,leading to low computing efficiency and high memory-occupation.To address this problem,a 2-stage pipeline is proposed for optimizing deep learning model inference on mobile devices with NNAs in terms of both speed and memory-footprint.The 1 st stage reduces computation workload via graph optimization,including splitting and merging nodes.The 2 nd stage goes further by optimizing at compilation level,including kernel fusion and in-advance compilation.The proposed optimizations on a commercial mobile phone with an NNA is evaluated.The experimental results show that the proposed approaches achieve 2.8×to 26×speed up,and reduce the memory-footprint by up to 75%.

关键词： machine learning inference neural network accelerator(NNA) low latency kernel fusion in-advance compilation

An open logic system admitting modification of inference rules

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Chinese Science Bulletin 1996年第13期41卷 1069-1071页

作者：应明生 Department of Mathematics Jiangxi Normal University Nanchang 330027 China

Recently, Li established an open logic system to describe growth and updating of knowledge and evolution of hypothesis. Afterwards, he used it to give a logical framework for knowledge base maintenance. In a knowledge... 详细信息

关键词： open logic system inference rule reconstruction.

Novel recursive inference algorithm for discrete dynamic Bayesian networks

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Progress in Natural Science:Materials International 2009年第9期19卷 1147-1151页

作者： Chris P. Thompson School of Engineering Cranfield University

Dynamic Bayesian networks (DBNs) can effectively perform modeling and qualitative reasoning for many dynamic systems. However, most of its inference algorithms involve complicated graphical transformations that are hard to program and time-consuming to compute. This article proposes a new recursive inference algorithm, which is a purely numerical method derived from probability theory and the characteristics of Bayesian networks to do both on-line and off-line inferences in discrete DBNs. The most prominent advantages of this novel approach include: (1) it is an exact inference algorithm, thus its accuracy and stability can be guaranteed, (2) it avoids the complex graphical transformation so as to remarkably improve the inference speed, and (3) its concise recursive formulae facilitate programming of both forwards and backwards pass. All of these issues are verified by accurate mathematical derivation as well as a couple of application examples with comparison between the new algorithm and the two most prevailing inference approaches of discrete DBNs - the interface algorithm and the forwards-backwards algorithm.

关键词： Discrete DBNs inference Algorithm

Improving Evidence-Based Practice in Forensic Medicine:Validation of INtegration of Forensic Epidemiology and the Rigorous EvaluatioN of Causation Elements and Principles of Evidence-Based Reporting in FORensic Medicine-Pathology version in Indonesia

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Journal of Forensic Science and Medicine 2023年第3期9卷 236-249页

作者： Putri Dianita Ika Meilia Herkutanto Agus Purwadianto Budi Sampurna Murdani Abdullah Diantha Soemantri Aria Kekalih Doctoral Program in Medical Sciences Faculty of Medicine Universitas IndonesiaJakartaIndonesia Department of Forensic Medicine and Mortuary Persahabatan General HospitalJakartaIndonesia Department of Forensic Medicine and Medicolegal Studies Dr.Cipto Mangunkusumo General HospitalFaculty of Medicine Universitas IndonesiaJakartaIndonesia Department of Internal Medicine Dr.Cipto Mangunkusumo General HospitalFaculty of Medicine Universitas IndonesiaJakartaIndonesia Department of Medical Education Faculty of Medicine Universitas IndonesiaJakartaIndonesia Department of Community Medicine Faculty of Medicine Universitas IndonesiaJakartaIndonesia

Introduction: Expert opinions presented in legal proceedings should be scientifically accountable, which is known as evidence-based practice (EBP). Although forensic medical expert opinions are essential in legal proceedings, the methods used to formulate them are not always evidence based or based on standard methods. In forensic medicine, EBP has not been explicitly applied, including in Indonesia. One potential approach to formulate evidence-based expert opinions is called INtegration of Forensic Epidemiology and the Rigorous EvaluatioN of Causation Elements (inference). In addition, there is also no universal guideline for making forensic pathological reports. One prospective guideline is named the Principles of Evidence-based Reporting in FORensic Medicine-Pathology version (PERFORM-P). Methods: This article describes the validation process of inference and PERFORM-P in Indonesia. This study uses a mixed method through three interrelated phases, i.e., (1) a cross-sectional survey to determine the characteristics of Indonesian forensic doctors and their current practice, (2) the adaptation and validation process of the two tools through a review by the Indonesian College of Forensic Medicine, and (3) a one-group pre-postintervention study to assess the validity and reliability of forensic medical expert opinions formulated using Indonesian-inference (i-inference) and reported using Indonesian-PERFORM-P (i-PERFORM-P). Results and Discussion: In general, both tools received a positive reception and can potentially be used in the Indonesian setting with some additions/clarifications in the user manuals. Participants envision that both tools will be most useful in complex cases. Conclusions: By obtaining the i-inference and the i-PERFORM-P, it is hoped that Indonesian forensic medical doctors are better equipped in analyzing and reporting complex cases, and the implementation of EBP can be improved.

关键词： Evidence-based practice forensic medicine forensic pathology inference Principles of Evidence-based Reporting in FORensic Medicine-Pathology version

Scalar Alternatives and Scalar inference Involving Adjectives:A Comment on van Tiel,et al.(2016)

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外国语 2019年第3期42卷 2-12页

作者： Louise McNally Universitat Pompeu Fabra

Doran, et al.(2009, 2012) and van Tiel, et al.(2016) have presented experimental evidence that gradable adjectives (e.***.cool) yield scalar inferences (e.***.to not cold) significantly less often than do numerals, quantifiers and modals;their data also reveal considerable variability within the class of adjectives in the frequency with which inferences are likely to be generated.Van Tiel, et al.consider two main explanations for this variation:differences among pairs of adjectives in what they call scale distinctness (how easy or difficult it is to differentiate the adjectives), and differences in scale availability (how salient the stronger scalar alternative is).They argue that only scale distinctness plays a role, and a rather small one at that;they leave most of the variation unexplained.In this comment, I argue that their measures of scale availability were too crude to detect a role for contextual variation in the scalar alternatives that subjects consider, but that this latter variation is, in fact, a very plausible part of the explanation for the results.I discuss some specific ways adjectives might yield different scalar alternatives in different contexts, under sufficiently sophisticated assumptions about their lexical semantics and about the rhetorical structure of discourse.

关键词： scalar implicature adjectives inference alternatives

A Computational Approach for Modeling the Allele Frequency Spectrum of Populations with Arbitrarily Varying Size

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Genomics, Proteomics & Bioinformatics 2019年第6期17卷 635-644页

作者： Hua Chen CAS Key Laboratory of Genomic and Precision Medicine Beijing Institute of GenomicsChinese Academy of SciencesBeijing 100101China CAS Center for Excellence in Animal Evolution and Genetics Chinese Academy of SciencesKunming 650223China School of Future Technology University of Chinese Academy of SciencesBeijing 100049China

The allele frequency spectrum(AFS), or site frequency spectrum, is commonly used to summarize the genomic polymorphism pattern of a sample, which is informative for inferring population history and detecting natural selection. In 2013, Chen and Chen developed a method for analytically deriving the AFS for populations with temporally varying size through the coalescence time-scaling function. However, their approach is only applicable to population history scenarios in which the analytical form of the time-scaling function is tractable. In this paper, we propose a computational approach to extend the method to populations with arbitrary complex varying size by numerically approximating the time-scaling function. We demonstrate the performance of the approach by constructing the AFS for two population history scenarios: the logistic growth model and the Gompertz growth model, for which the AFS are unavailable with existing approaches. Software for implementing the algorithm can be downloaded at http://***/software/.

关键词： Allele frequency spectrum Complex demography Population history Population genetic inference Coalescent