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1.
    
The scarcity of training annotation is one of the major challenges for the application of deep learning technology in medical image analysis. Recently, self-supervised learning provides a powerful solution to alleviate this challenge by extracting useful features from a large number of unlabeled training data. In this article, we propose a simple and effective self-supervised learning method for leukocyte classification by identifying the different transformations of leukocyte images, without requiring a large batch of negative sampling or specialized architectures. Specifically, a convolutional neural network backbone takes different transformations of leukocyte image as input for feature extraction. Then, a pretext task of self-supervised transformation recognition on the extracted feature is conducted by a classifier, which helps the backbone learn useful representations that generalize well across different leukocyte types and datasets. In the experiment, we systematically study the effect of different transformation compositions on useful leukocyte feature extraction. Compared with five typical baselines of self-supervised image classification, experimental results demonstrate that our method performs better in different evaluation protocols including linear evaluation, domain transfer, and finetuning, which proves the effectiveness of the proposed method.  相似文献   

2.
张良  谈攀  洪亮 《生物工程学报》2025,41(3):934-948
蛋白质突变效应预测是生物信息学和蛋白质工程领域的一个关键挑战。近年来,深度学习,特别是蛋白质语言模型的发展为该领域带来了新的机遇。本文综述了蛋白质语言模型在蛋白质突变效应预测中的应用,重点讨论了3类主要模型:基于序列的模型、基于结构的模型以及结合序列和结构信息的模型,详细分析了这些模型的原理、优势和局限性,并探讨了无监督学习和监督学习在模型训练中的应用。此外,还讨论了当前面临的主要挑战,包括高质量数据集的获取、数据噪声的处理等。最后,展望了未来研究方向,包括多模态融合、少样本学习等新兴技术的应用前景。本综述为研究者提供了一个全面的视角,以推动蛋白质突变效应预测领域的进一步发展。  相似文献   

3.
细胞中自发或由酶催化的代谢反应组成了高度复杂的代谢网络,其与细胞生理代谢活动运作密切相关。细胞生理代谢网络模型的重构有助于从系统层面上解析基因型与生长表型之间的关联,为细胞生理代谢活动精准刻画与生物绿色制造等研究提供重要的计算生物学工具。本文系统介绍了全基因组尺度代谢网络模型(genome-scale metabolic models, GEMs)、动力学模型、酶约束代谢模型(enzyme-constrained genome-scale metabolic models, ecGEMs)等不同类型细胞生理代谢网络模型发展与应用的最新研究进展;同时还介绍了GEMs自动化构建研究进展以及条件特异性GEMs建模策略。人工智能技术为高精度细胞生理代谢网络模型构建提供了全新机遇,本文进一步总结了人工智能技术在动力学模型和酶约束模型构建等领域的应用。各类细胞生理代谢网络模型的高质量重构将为今后的定量合成生物学与系统生物学等研究提供强大计算支撑。  相似文献   

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A small herd of captive sable antelope (Hippotragus niger) was observed repeatedly while progressing through a gate connecting a pasture to a corral. The ordinal position of each herd member was recorded during each progression. These data were analyzed quantitatively with respect to three models of progression order control and one of random ordering. An end point-control model, stating that the oldest female of a progression occupies the first position while the remainder of the animals randomly distribute themselves within the progression, accounts for the data. These results are related to both protection and resource learning theories of progression order. The terminology used in the study of leadership and ordinal progressions is discussed as well.  相似文献   

7.
  总被引:1,自引:0,他引:1  
The degree of influence of environment, location and geography on the distribution of closely-related Jekelius nitidus and Jekelius hernandezi , coleopteran species endemic to the Iberian Peninsula, was examined. Niche envelope model predictions of probable absence points were based on available presence information. Presence–absence information for each of the two species was logistic-regressed against climate, altitude, lithology, spatial and river basin variables from each of 100 km2 UTM Iberian Peninsula squares. Models predict that environmental conditions are suitable for both species in an area larger than that in which they have been found. The best-fitting environment model for J. nitidus , based on summer precipitation, area underlain by siliceous rocks, area with siliceous sediments and aridity index, explains more than 81% of total deviance. The final model, which includes spatial and river basin variables, accounts for nearly of 89% of total deviance. The best-fitting environment model for J. hernandezi, based on the area underlain by calcareous rocks, summer precipitation, aridity index, altitude and minimum annual temperature, explains 63% of total deviance. The final model based on both spatial and river basin variables accounts for nearly 70% of total deviance.
  Our results suggest that climate influences the distribution of both species similarly and that the acidic or basic nature of the substrate is the environment variable that most influences the occurrence of both species. The major degree of influence of river basin variables, together with lithologic variables, on the current distribution of both species may be due to the limited mobility of these flightless species.  相似文献   

8.
  总被引:1,自引:0,他引:1  
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9.
    
Tuberculosis (TB) kills approximately 1.6 million people yearly despite the fact anti-TB drugs are generally curative. Therefore, TB-case detection and monitoring of therapy, need a comprehensive approach. Automated radiological analysis, combined with clinical, microbiological, and immunological data, by machine learning (ML), can help achieve it.  相似文献   

10.
Abstract Much of biogeography, conservation and evolutionary biology, and ecology involves very large spatial and temporal extents. Direct manipulation to test hypotheses is usually almost impossible at appropriate scales so that multivariate modelling and especially regression are used to draw causal inferences about which ‘independent’ variables influence the distribution and abundances of species. Such inferences clearly are crucial for the successful management of biological resources and for conserving threatened species. A succession of regression approaches has arisen, many of which yield inconsistent implications. The main problem has been the quest for one (the ‘best’ or the ‘optimal’) regression model from which the impacts of independent variables are inferred. This note is to draw the attention of ecologists to a relatively recent method, hierarchical partitioning, that does not aim to identify a best regression model as such but rather uses all models in a regression hierarchy to distinguish those variables that have high independent correlations with the dependent variable. Such variables are likely to be most influential in controlling variation in the dependent variable. Hierarchical partitioning is not to be regarded as a substitute for experimental manipulation when that is appropriate, but it is likely to produce better deductions than common regression approaches in the many ecological situations in which manipulation is impossible or of doubtful value.  相似文献   

11.
Creutzfeldt-Jakob disease (CJD) is a kind of rare, rapidly progressive fatal central nervous system disorders. In China, the surveillance for CJD has started since 2006. As one of the major issues in CJD surveillance, the follow-up process via telephone plays important role in CJD diagnosis and surveillance. Although the follow-up process was conducted by the experiential staffs from CJD surveillance center in China CDC, it is frequently encountered that some interviewed family members do not cooperate well during follow-up. To screen the possible factors influence on the compliances of the interviewees during CJD follow-up, 11 independent variables from patient aspect and 4 variables from interviewee aspect were selected and a questionnaire was prepared. Based on 199 suspected sporadic CJD cases reported to CJD surveillance center in 2013, a telephone-inquiring was conducted and the degree of compliances of the interviewees were given as good, fair or poor. After screened with univariate analysis and evaluated ordinal logistic regression analysis, several indictors, such as the patient gender, CJD diagnosis, numbers of clinical symptoms, continual medical treatment after diagnosis, medical treatment mode, as well as the relationship with the patient and CJD knowledge of the interviewees, showed influence on the compliance in CJD follow-up process significantly. The data here provide for the first time the factors related with the compliances of the interviewed family members of the suspected CJD patients during follow-up process, which supplies useful clue for us to improve CJD follow-up process and increase the capacity of CJD surveillance.  相似文献   

12.
Phylogenetic information is becoming a recognized basis for evaluating conservation priorities, but associations between extinction risk and properties of a phylogeny such as diversification rates and phylogenetic lineage ages remain unclear. Limited taxon-specific analyses suggest that species in older lineages are at greater risk. We calculate quantitative properties of the mammalian phylogeny and model extinction risk as an ordinal index based on International Union for Conservation of Nature Red List categories. We test for associations between lineage age, clade size, evolutionary distinctiveness and extinction risk for 3308 species of terrestrial mammals. We show no significant global or regional associations, and three significant relationships within taxonomic groups. Extinction risk increases for evolutionarily distinctive primates and decreases with lineage age when lemurs are excluded. Lagomorph species (rabbits, hares and pikas) that have more close relatives are less threatened. We examine the relationship between net diversification rates and extinction risk for 173 genera and find no pattern. We conclude that despite being under-represented in the frequency distribution of lineage ages, species in older, slower evolving and distinct lineages are not more threatened or extinction-prone. Their extinction, however, would represent a disproportionate loss of unique evolutionary history.  相似文献   

13.
    
Radiogenomics is a field where medical images and genomic profiles are jointly analyzed to answer critical clinical questions. Specifically, people want to identify non-invasive imaging biomarkers that are associated with both genomic features and clinical outcomes. Deep learning is an advanced computer science technique that has been applied in many fields, including medical image and genomic data analysis. This review summarizes the current state of deep learning in pan-cancer radiogenomic research, discusses its limitations, and indicates the potential future directions. Traditional machine learning in radiomics, genomics, and radiogenomics have also been briefly discussed. We also summarize the main pan-cancer radiogenomic research resources. Two characteristics of deep learning are emphasized when discussing its application to pan-cancer radiogenomics, which are extendibility and explainability.  相似文献   

14.
The application of GIS-modelling to mustelid landscape ecology   总被引:1,自引:0,他引:1  
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15.
    
Despite the economic importance of beef cattle production in Brazil, female reproductive performance, which is strongly associated with production efficiency, is not included in the selection index of most breeding programmes due to low heritability and difficulty in measure. The body condition score (BCS) could be used as an indicator of these traits. However, so far little is known about the feasibility of using BCS as a selection tool for reproductive performance in beef cattle. In this study, we investigated the sources of variation in the BCS of Nellore beef cows, quantified its association with reproductive and maternal traits and estimated its heritability. BCS was analysed using a logistic model that included the following effects: contemporary group at weaning, cow weight and hip height, calving order, reconception together with the weight and scores of conformation and early finishing assigned to calves at weaning. In the genetic analysis, variance components of BCS were estimated through Bayesian inference by fitting an animal model that also included the aforementioned effects. The results showed that BCS was significantly associated with all of the reproductive and maternal variables analysed. The estimated posterior mean of heritability of BCS was 0.24 (highest posterior density interval at 95%: 0.093 to 0.385), indicating an involvement of additive gene action in its determination. The present findings show that BCS can be used as a selection criterion for Nellore females.  相似文献   

16.
    
Large‐scale agreement studies are becoming increasingly common in medical settings to gain better insight into discrepancies often observed between experts' classifications. Ordered categorical scales are routinely used to classify subjects' disease and health conditions. Summary measures such as Cohen's weighted kappa are popular approaches for reporting levels of association for pairs of raters' ordinal classifications. However, in large‐scale studies with many raters, assessing levels of association can be challenging due to dependencies between many raters each grading the same sample of subjects' results and the ordinal nature of the ratings. Further complexities arise when the focus of a study is to examine the impact of rater and subject characteristics on levels of association. In this paper, we describe a flexible approach based upon the class of generalized linear mixed models to assess the influence of rater and subject factors on association between many raters' ordinal classifications. We propose novel model‐based measures for large‐scale studies to provide simple summaries of association similar to Cohen's weighted kappa while avoiding prevalence and marginal distribution issues that Cohen's weighted kappa is susceptible to. The proposed summary measures can be used to compare association between subgroups of subjects or raters. We demonstrate the use of hypothesis tests to formally determine if rater and subject factors have a significant influence on association, and describe approaches for evaluating the goodness‐of‐fit of the proposed model. The performance of the proposed approach is explored through extensive simulation studies and is applied to a recent large‐scale cancer breast cancer screening study.  相似文献   

17.
  总被引:1,自引:0,他引:1  
Albert PS 《Biometrics》2007,63(2):593-602
Estimating diagnostic accuracy without a gold standard is an important problem in medical testing. Although there is a fairly large literature on this problem for the case of repeated binary tests, there is substantially less work for the case of ordinal tests. A noted exception is the work by Zhou, Castelluccio, and Zhou (2005, Biometrics 61, 600-609), which proposed a methodology for estimating receiver operating characteristic (ROC) curves without a gold standard from multiple ordinal tests. A key assumption in their work was that the test results are independent conditional on the true test result. I propose random effects modeling approaches that incorporate dependence between the ordinal tests, and I show through asymptotic results and simulations the importance of correctly accounting for the dependence between tests. These modeling approaches, along with the importance of accounting for the dependence between tests, are illustrated by analyzing the uterine cancer pathology data analyzed by Zhou et al. (2005).  相似文献   

18.
    
Human dimensions research is valuable to managing human-wildlife interactions, especially in urban environments where such interactions are common. Survey data, which commonly contain Likert scales and questions, are useful in this field; however, these data can be difficult to analyze with formal modeling approaches. We demonstrate one approach, based on hierarchical Bayesian ordinal regression, to evaluate human-coyote relationships in Rhode Island, USA. We implemented a survey to collect demographic and sociocultural characteristics of Rhode Island residents and information related to their knowledge of and experiences with coyotes. Our objectives were to assess how these characteristics affected respondents' valuation of and interactions (sightings and incidents) with coyotes. We analyzed 980 surveys from October to December 2020. We found that respondents who had fear of coyotes or experienced an incident between an owned animal and coyote, had the lowest valuation of coyotes. The same demographic of respondents also reported the highest sightings of and incidents with coyote. These results indicate that fearful residents, in addition to pet and livestock owners, are priority targets for disseminating information or programming about coyotes. Our analyses and findings demonstrate how Bayesian ordinal regression can provide clear and appropriate inference from survey data on how groups of people vary in their relationship with wildlife. These results are important in effectively and efficiently allocating resources towards mitigation, education, and management of human-wildlife interactions.  相似文献   

19.
    
Abstract I provide a brief introduction to the concept of spatial autocorrelation and its incorporation into regression-type models. Spatial autocorrelation occurs when the response variable is correlated with itself at other locations in the region of interest. The autocorrelation usually takes a specific form where observations close in space are more correlated than those farther apart, and the rate of decay of the correlation is a function of the distance separating 2 locations. I present 2 commonly used models: 1) geostatistical modeling in which data are collected at points in the study region and 2) conditional autoregression (lattice) models in which data are aggregated over small nonoverlapping sub-areas of the study region. I also describe incorporation of explanatory covariates, such as habitat or physico-chemical attributes. I emphasize frequentist methods, but I briefly describe Bayesian approaches. I also provide some advantages, such as obtaining correct standard errors for estimators, and disadvantages, such as requirements for larger sample sizes, of incorporating spatial autocorrelation into the modeling effort. This information can aid researchers in designing and analyzing models of the relationships between species distributions and habitat. As a result, more informative models can be developed which further aid in management of wildlife.  相似文献   

20.
殷宗俊  张勤  张纪刚  丁向东 《遗传学报》2005,32(11):1147-1155
在广义线性模型的框架内模拟研究了家畜抗性等级性状的QTL定位方法,QTL参数的估计采用最大似然方法,比较了阈模型方法与一般线性方法的QTL定位效率,并对影响等级性状QTL定位效率的主要因素(QTL效应、性状的遗传力)进行了模拟研究,实验设计为多个家系的女儿设计,资源群体大小为500头。研究结果表明:在QTL位置参数估计及检验功效方面,阈模型方法具有一定的优势,对抗性等级性状QTL定位的功效也高于线性方法。另外,性状遗传力和QTL效应的大小对QTL定位的准确度也有直接的影响,随着性状遗传力QTL效应的  相似文献   

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