Capture-recapture, epidemiology, and list mismatches: two lists

In recent years, capture-recapture methods for closed populations have been extensively applied to epidemiology. For example, suppose we have several incomplete lists of diabetics and we wish to estimate the total number of diabetics by estimating the number missing from all the lists. A major problem is that the information about individuals on the lists may have been given incorrectly or the information may have been typed incorrectly so that some list matches are missed. Using the concept of tag loss borrowed from animal population studies, we consider methods for estimating both the probabilities of making list errors and the population size for just two independent lists. The effect of heterogeneity on the errors is examined. The methods are applied to a large data set of diabetic persons consisting of a list obtained from a survey and a list obtained from doctors' records. It was found that the error rates were high and that ignoring the errors led to a gross overestimate of the total number of diabetic persons.     

A Multilevel Model for Continuous Time Population Estimation

Summary .  Statistical methods have been developed and applied to estimating populations that are difficult or too costly to enumerate. Known as multilist methods in epidemiological settings, individuals are matched across lists and estimation of population size proceeds by modeling counts in incomplete multidimensional contingency tables (based on patterns of presence/absence on lists). As multilist methods typically assume that lists are compiled instantaneously, there are few options available for estimating the unknown size of a closed population based on continuously (longitudinally) compiled lists. However, in epidemiological settings, continuous time lists are a routine byproduct of administrative functions. Existing methods are based on time-to-event analyses with a second step of estimating population size. We propose an alternative approach to address the twofold epidemiological problem of estimating population size and of identifying patient factors related to duration (in days) between visits to a health care facility. A Bayesian framework is proposed to model interval lengths because, for many patients, the data are sparse; many patients were observed only once or twice. The proposed method is applied to the motivating data to illustrate the methods' applicability. Then, a small simulation study explores the performance of the estimator under a variety of conditions. Finally, a small discussion section suggests opportunities for continued methodological development for continuous time population estimation.     

A comparative analysis of global, national, and state red lists for threatened amphibians in Brazil

The knowledge about the conservation status of species is an important data for conservation biology. Therefore, threatened species lists are a powerful tool for conservation planning and prioritization. Our objective is to compare the global, the national and state red lists of amphibians in Brazil. Threatened species were categorized according to their listing in one or several of these lists. We analyzed for true inconsistencies across lists in order to evaluate practical consequences of such incongruences on amphibian conservation in Brazil. We recorded a total of 61 threatened amphibian species in Brazil (across all red lists). Only one species, Phrynomedusa fimbriata, was listed as Extinct (both in IUCN, Brazil and S?o Paulo lists). A total of eleven endemic species are listed as threatened by the global red list, but do not appear in Brazil’s national red list, which represent an inconsistence among these lists. Besides that, the threat category of Thoropa lutzi and Thoropa petropolitana, two endemic species, differ among both lists, which also represents a problem between both lists. These mismatches may be due to several reasons such as different interpretation of the criteria; different methodologies used; different data availability on species; differences in the dates of assessments processes; the assessors’ attitudes to uncertainty; outdated red lists. Harmonization among red lists permits a better picture of threatened amphibian diversity across scales and to develop global, national and state plans to complement conservation actions in order to maximize the chance of success of these initiatives.     

Multilist population estimation with incomplete and partial stratification

Multilist capture-recapture methods are commonly used to estimate the size of elusive populations. In many situations, lists are stratified by distinguishing features, such as age or sex. Stratification has often been used to reduce biases caused by heterogeneity in the probability of list membership among members of the population; however, it is increasingly common to find lists that are structurally not active in all strata. We develop a general method to deal with cases when not all lists are active in all strata using an expectation maximization (EM) algorithm. We use a flexible log-linear modeling framework that allows for list dependencies and differential probabilities of ascertainment in each list. Finally, we apply our method of estimating population size to two examples.     

Capture–recapture analysis with a latent class model allowing for local dependence and observed heterogeneity

In epidemiology, capture–recapture models are commonly used to estimate the size of an unknown population based on several incomplete lists of individuals. The method operates under two main assumptions: independence between the lists (local independence) and homogeneity of capture probabilities of individuals. In practice, these assumptions are rarely satisfied. We introduce a multinomial latent class model that can account for both list dependence and heterogeneity. Parameter estimation is performed by maximizing the conditional likelihood function with the use of the EM algorithm. In addition, a new approach for evaluating the standard errors of the parameter estimates is discussed, which considerably reduces the computational burden associated with the evaluation of the variance of the population size estimate.     

Effect of list errors on the estimation of population size

In many situations, it is possible to estimate the size of a closed population if some members of the population are recorded on one or more administrative lists. An important example is estimating the prevalence of a disease, where some members of the disease population may be recorded on lists such as disease registries, hospital admission records, and general practitioner records. An incomplete contingency table is formed by matching the lists and the missing cell count estimated by prediction based on a fitted model, which assumes that the matching is done without error. In practice, matching errors do occur, and in this article, we examine the effect of these errors on the estimation process and show how the standard models may be modified to allow for matching errors.     

Using simple species lists to monitor trends in animal populations: new methods and a comparison with independent data

There is an urgent need to develop simple and inexpensive methods for monitoring wildlife populations in resource-poor countries. List-based methods have been advocated as simple yet potentially useful biodiversity monitoring tools, and systems have recently been launched in a number of countries to collect species lists. We attempt to advance the use of systematic list-based monitoring by (1) suggesting improvements to the way in which list reporting rates are calculated; (2) assessing the extent to which degrading effort-corrected measures of abundance into simple species lists results in loss of information on population trends; (3) comparing long-term trends in list reporting rates with population trends from a wholly independent monitoring scheme. Daily species lists of birds were derived from regular trapping at a nature reserve in southern England. Most species showed a strong correlation across years between the proportion of lists on which they occurred, adjusted for list length (adjusted list reporting rate; ALRR), and an effort-corrected measure of abundance (captures per unit effort; CPUE). ALRR revealed almost as much about annual variation in abundance as CPUE for all but the most frequently captured species. Long-term (>20 years) trends in ALRRs at the nature reserve were positively correlated with UK national population trends recorded over the same period by an independent, labour-intensive monitoring scheme that counted birds at a large number of widely spread sites. Our results support previous claims that simple species lists could generate data useful for monitoring long-term population trends, particularly where such lists are collected systematically. However, further research on the efficiency of list reporting rates relative to more sophisticated methods is necessary, before list-based methods can be advocated for dedicated monitoring schemes in resource-poor regions.     

Network selection: a method for ranked lists selection

We consider the problem of finding the set of rankings that best represents a given group of orderings on the same collection of elements (preference lists). This problem arises from social choice and voting theory, in which each voter gives a preference on a set of alternatives, and a system outputs a single preference order based on the observed voters' preferences. In this paper, we observe that, if the given set of preference lists is not homogeneous, a unique true underling ranking might not exist. Moreover only the lists that share the highest amount of information should be aggregated, and thus multiple rankings might provide a more feasible solution to the problem. In this light, we propose Network Selection, an algorithm that, given a heterogeneous group of rankings, first discovers the different communities of homogeneous rankings and then combines only the rank orderings belonging to the same community into a single final ordering. Our novel approach is inspired by graph theory; indeed our set of lists can be loosely read as the nodes of a network. As a consequence, only the lists populating the same community in the network would then be aggregated. In order to highlight the strength of our proposal, we show an application both on simulated and on two real datasets, namely a financial and a biological dataset. Experimental results on simulated data show that Network Selection can significantly outperform existing related methods. The other way around, the empirical evidence achieved on real financial data reveals that Network Selection is also able to select the most relevant variables in data mining predictive models, providing a clear superiority in terms of predictive power of the models built. Furthermore, we show the potentiality of our proposal in the bioinformatics field, providing an application to a biological microarray dataset.     

Discovering topological motifs using a compact notation.

Discovering topological motifs or common topologies in one or more graphs is an important as well as an interesting problem. It had been classically viewed as the subgraph isomorphism problem. This problem and its various flavors are known to be NP-Complete. However, this does not minimize the importance of solving this problem accurately in application areas such as bioinformatics or even larger network studies. The explosion in the size of the output is usually caused by isomorphisms in the motif or graph: we present a method to handle this without sacrificing the correct answers. In this paper, we apply the natural notion of maximality, used extensively in strings, to graphs and present a simple three-step approach to solving this problem completely and exactly (without resorting to heuristics). We handle the natural combinatorial explosion due to isomorphisms inherent in the problem (which could result in output size being exponential in the input size) by the use of "compact location lists." In other words, instead of enumerating k elements out of n, we use the ((n)(k)) form in an implicit manner (k immediate neighbors of a vertex out of n possible immediate neighbors). This drastically reduces the size of the output without any loss of information. The algorithm we present is linear in terms of the size of the output encoded as compact lists.     

Exploiting genomics,genetics and chemistry to combat antibiotic resistance

To address the worsening problem of antibiotic-resistant bacteria there is an urgent need to develop new antibiotics. Comparative genomics and molecular genetics are being applied to produce lists of essential new targets for compound screening programmes. Combinatorial chemistry and structural biology are being applied to rapidly explore and optimize the interactions between lead compounds and their biological targets. Several compounds that have been identified from target-based screens are now in development, but technical and economic constraints might result in a trickle, rather than a flood, of new antibiotics onto the market in the near future.     

Preliminary results of a district call scheme for cervical screening organised in general practice.

A recognised problem with the cervical screening programme in the United Kingdom is the failure to include women who have never had a cervical smear test, who are a high risk group. The implementation of a district based call scheme in East Berkshire in 1986 is described whereby women aged 20-64 with no record of a cervical smear test who were judged to be eligible for testing by their general practitioner were sent a personal invitation from their general practitioner to attend for a test. A list of high risk unscreened women was kept by each practice, and a duplicate sent to the cytology laboratory to update the central records. Six months after each batch of invitations had been sent the resulting number of women having a smear test was assessed. Forty three of 51 practices approached agreed to participate in the five year scheme. During the first year lists were sent to the 43 participating practices. The first list was returned to the cytology laboratory by 37 practices and the second by 33; practices varied in their responses, however, some needing considerable persuasion to return the lists. Of 972 identified unscreened women from the total 3757 women listed in the lists of the family practitioner committee, 247 (25%) had a cervical smear test in response to the invitation, representing an overall increase of 7% in the screened population. The preliminary findings of the five year study have shown that screening can be improved by a systematic call scheme. Coordinated support from the area health authority in health education, monitoring of screening, and feedback of data from the scheme to practices is required to reduce the proportion of unscreened women.     

Finding cancer biomarkers from mass spectrometry data by decision lists.

Finding accurate biomarkers is key to early diagnosis and successful treatment of many otherwise incurable diseases. In this work, we study the problem of finding biomarkers through mass spectrometry (SELDI-TOF) spectra from cancerous and normal tissues. In contrast to the common practice of using vague methods such as genetic algorithms, or uninterpretable methods such as Support Vector Machines, we look for a method that is simple, intuitive, interpretable, usable, and more accurate. We introduce decision lists to this domain. Our experiments on clinical cancer datasets demonstrate that decision lists can achieve more accurate results than other methods. More interestingly, the resulting decision lists are more interpretable for possible causal relationship between cancer and differentially expressed proteins, and directly usable in clinical biomarker design. In particular, our approach is capable of finding multiple biomarkers with high sensitivity and specificity. Such a feature will provide clues for medical experts to thoroughly investigate the roles of protein in cancer development and progression.     

Melanopsin,ganglion-cell photoreceptors,and mammalian photoentrainment

An understanding of the retinal mechanisms in mammalian photoentrainment will greatly facilitate optimization of the wavelength, intensity, and duration of phototherapeutic treatments designed to phase shift endogenous biological rhythms. A small population of widely dispersed retinal ganglion cells projecting to the suprachiasmatic nucleus in the hypothalamus is the source of the critical photic input. Recent evidence has shown that many of these ganglion cells are directly photosensitive and serve as photoreceptors. Melanopsin, a presumptive photopigment, is an essential component in the phototransduction cascade within these intrinsically photosensitive ganglion cells and plays an important role in the retinal photoentrainment pathway. This review summarizes recent findings related to melanopsin and melanopsin ganglion cells and lists other retinal proteins that might serve as photopigments in the mammalian photoentrainment input pathway.     

Causality,menopause, and depression: a critical review of the literature.

OBJECTIVE: To assess whether causal criteria can be used to find out whether there is support in published research for maintaining that menopause causes depression. DESIGN: Ninety four articles from 30 years of research examining the relation of natural menopause to depression were traced by using Medline and systematic follow up of reference lists. Specified exclusion and inclusion criteria were applied, and the resulting 43 epidemiological primary research articles were classified and tabulated according to sample and measures used and the researchers'' own conclusion as to whether or not an association had been established. This material was qualitatively evaluated with Hill''s nine criteria for causality. RESULT: There is insufficient evidence at present to maintain that menopause causes depression. In addition to methodological and statistical problems, a temporal problem in the menopause concept hinders research in this area. CONCLUSION: Causal criteria can usefully be used to structure a literature review. Further theoretical work is required to integrate standard clinical epidemiological concepts.     

A genetic-demographic approach in anthropological research. VI. The methodological aspects of collecting, storing and analyzing large blocks of genealogical and biodemographic data

A new method of collection and presentation of the genealogical data in nontraditional (nongraphic) way is proposed. The collection of genealogical data within a population is organized through the family lists presented in perforated cards. The quick and correct identification of any population member realizes by colour tab indexes. The principles of arrangement and algorithms of organization of population tab card system are described.     

Rhesus monkeys (Macaca mulatta) show robust primacy and recency in memory for lists from small, but not large, image sets

The combination of primacy and recency produces a U-shaped serial position curve typical of memory for lists. In humans, primacy is often thought to result from rehearsal, but there is little evidence for rehearsal in nonhumans. To further evaluate the possibility that rehearsal contributes to primacy in monkeys, we compared memory for lists of familiar stimuli (which may be easier to rehearse) to memory for unfamiliar stimuli (which are likely difficult to rehearse). Six rhesus monkeys saw lists of five images drawn from either large, medium, or small image sets. After presentation of each list, memory for one item was assessed using a serial probe recognition test. Across four experiments, we found robust primacy and recency with lists drawn from small and medium, but not large, image sets. This finding is consistent with the idea that familiar items are easier to rehearse and that rehearsal contributes to primacy, warranting further study of the possibility of rehearsal in monkeys. However, alternative interpretations are also viable and are discussed.     

Development,databases and the internet

There is now a rapidly expanding population of interlinked developmental biology databases on the World Wide Web that can be readily accessed from a desk-top PC using programs such as Netscape or Mosaic. These databases cover popular organisms (Arabidopsis, Caenorhabditis, Drosophila, zebrafish, mouse, etc.) and include gene and protein sequences, lists of mutants, information on resources and techniques, and teaching aids. More complex are databases relating domains of gene expression to embryonic anatomy and these range from existing text-based systems for specific organs such as kidney, to a massive project under development, that will cover gene expression during the whole of mouse embryogenesis. In this brief article, we review selected examples of databases currently available, look forward to what will be available soon, and explain how to gain access to the World Wide Web.     

Birds as surrogates for biodiversity: An analysis of a data set from southern Québec

Surrogacy analysis consists of determining a set of biotic or environmental parameters which can be rapidly assessed in the field and reliably used to prioritize places for biodiversity conservation. Whether adequate surrogate sets exist remains an open and relatively unexplored question though its solution is central to the aims of conservation biology. This paper analyses the surrogacy problem by prioritizing places using surrogate lists and comparing these results with those obtained by using more comprehensive species lists. More specifically, it explores (i) the possibility of using bird distributions, which are often easily available, as surrogates for species at risk (endangered and threatened species), which are presumed to be an important component of biodiversity; and (ii) the methodological question of how spatial scale influences surrogate success. The data set analysed, from southern Québec, is one of the most complete biotic data sets available at the regional scale. Contrary to some previous analyses, the results obtained suggest that the surrogacy problem is potentially solvable.     

Energetic metabolism,stress, and immunity—development of population physiology

This review shows that the interpenetration of population ecology and animal physiology positively affects the both scientific directions that are important fields of modern zoology. Due to progress in the development of telemetry and non-invasive methods to assess the animal state, as well as of moleculargenetic methods that permit to distinguish the markers reflecting the individual history of an individual, the possibilities of studying responses of an organism to environmental impacts have been greatly expanded. The combined use of traditional ecological and modern physiological, immunological, and molecular-genetic methods promotes to reveal mechanisms responsible for the stable existence of population in the dynamic environment. In addition, the analysis of the contribution of physiological and immunological processes to the formation of adaptations on the population level is a requirement to understand their adaptive importance, which is not always evident when considering a problem at the organism-centric level.     

AGRA: analysis of gene ranking algorithms

Often, the most informative genes have to be selected from different gene sets and several computer gene ranking algorithms have been developed to cope with the problem. To help researchers decide which algorithm to use, we developed the analysis of gene ranking algorithms (AGRA) system that offers a novel technique for comparing ranked lists of genes. The most important feature of AGRA is that no previous knowledge of gene ranking algorithms is needed for their comparison. Using the text mining system finding-associated concepts with text analysis. AGRA defines what we call biomedical concept space (BCS) for each gene list and offers a comparison of the gene lists in six different BCS categories. The uploaded gene lists can be compared using two different methods. In the first method, the overlap between each pair of two gene lists of BCSs is calculated. The second method offers a text field where a specific biomedical concept can be entered. AGRA searches for this concept in each gene lists' BCS, highlights the rank of the concept and offers a visual representation of concepts ranked above and below it. AVAILABILITY AND IMPLEMENTATION: Available at http://agra.fzv.uni-mb.si/, implemented in Java and running on the Glassfish server. CONTACT: simon.kocbek@uni-mb.si.