Research Resources

The Irish LongituDinal Study on Ageing (TILDA) is a study of a representative cohort of over 8500 people resident in Ireland aged 50+, charting their health, social and economic circumstances over a 10-year period. The second wave of data collection was completed this year. TILDA is unique amongst longitudinal studies internationally in the breadth of physical, mental health and cognitive measures collected.

In order to establish a sustainable social security system in Japan, whose population is aging ahead of other developed countries, it is crucial to make available micro-data on the diverse aspects of the lives of elderly people. Extensive surveys have been conducted on elderly people in many other countries, and the resulting data have been utilized not only for academic and research purposes, but also as a valuable input for real-world policymaking. Despite the rapid aging of the Japanese population, no statistical survey that could properly capture the diversity of the elderly population from various viewpoints had been carried out in Japan until recently.

Against this backdrop, RIETI and Hitotsubashi University jointly launched a comprehensive survey of elderly people in 2007 to collect panel data on their lives and health, with the University of Tokyo joining from 2009 onward. The data collected in this survey include diverse information on the economic, social, and health conditions of elderly people. In addition, the survey is designed to ensure, to the maximum extent possible, comparability with preceding surveys such as the Health and Retirement Study in the United States, the Survey of Health, Aging and Retirement in Europe in continental Europe, and the English Longitudinal Study of Aging in the United Kingdom. Therefore, by analyzing JSTAR data, researchers can track the characteristics of the Japanese elderly population in terms of both their specificity and universality in the world. In this sense, JSTAR is Japan's first-ever globally comparable panel data survey of elderly people.

The Mexican Health and Aging Study (MHAS) started as a prospective panel study of health and aging in Mexico. The MHAS study will design, field, and disseminate the data to achieve research goals that include: examining the aging processes and its disease and disability burden in a large representative panel of older Mexicans; evaluating the effects of individual behaviors, early life circumstances, migration and economic history, community characteristics, and family transfer systems on multiple health outcomes; comparing the health dynamics of older Mexicans with comparably aged Mexican-born migrants in the U.S. and second-generation Mexican-Americans using similar data from the U.S. population (for example the biennial Health and Retirement Study) to assess the durability of the migrant health advantage; assess the health of all components of the population from which migrants are selectively recruited; and considering ways in which intergenerational transfer systems affect old-age health dynamics in a country where migration is commonplace and remittances may repay prior investments or ensure against uncertainty in old age.

The Vietnam Era Twin Study of Aging (VETSA) is a large-scale investigation of cognitive aging from middle to later age. The intended sample was recruited from the Vietnam Era Twin Registry (VETR), a registry of middle-aged male-male twin pairs who both served in the United States military during the Vietnam conflict (1965-1975). VETSA employs a multitrait, multimethod approach to cognitive assessment to focus on the genetic and environmental contributions to cognitive processes over time, as well as the relative contributions to cognitive aging from health, social, personality, and other contextual factors.

The Wisconsin Longitudinal Study (WLS) is a long-term study of a random sample of 10,317 men and women who graduated from Wisconsin high schools in 1957. The WLS provides an opportunity to study the life course, intergenerational transfers and relationships, family functioning, physical and mental health and well-being, and morbidity and mortality from late adolescence through 2008. WLS data also cover social background, youthful aspirations, schooling, military service, labor market experiences, family characteristics and events, social participation, psychological.

VennPlex is a novel Venn diagram generating tool that can separate factors between two to four input datasets. VennPlex has been designed to separate data which possesses a sortable denominator (e.g. official Gene Symbol) with an associated variable numerator (e.g. z-ratio value). VennPlex can separate denominators between sets and also demonstrate the differences in the numerator values for denominators common to multiple set intersections that possess distinct numerical values. Read more about VennPlex and download the file. 

VENNTURE is a novel Venn diagram-generating tool that can accommodate the input of up to 6 distinct data sets from an Excel spreadsheet. VENNTURE allows Venn diagram set image generation with additional intersection data representation viewing modes. The Venn segment contents can either be viewed in the VENNTURE Venn diagram image itself or they can be exported to an annotated Excel spreadsheet.

This software is available for download and is contained in a Winzip file along with the NIH Software Transfer Agreement and a PDF formatted copy of the journal article. Download the VENNTURE ZIP file. Please cite the following paper when employing this tool in publications or other forms of media:

Martin B, Chadwick W, Yi T, Park SS, Lu D, Ni B, Gadkaree S, Farhang K, Becker KG, Maudsley S.  VENNTURE–A Novel Venn Diagram Investigational Tool for Multiple Pharmacological Dataset Analysis.  PLoS ONE 10.1371/journal.pone.0036911

WND-CHARM is an acronym that stands for "Weighted Neighbor Distance using Compound Hierarchy of Algorithms Representing Morphology.  "WND-CHARM is a multi-purpose image classifier that can be applied to a wide variety of image classification tasks without modifications or fine-tuning, and yet provides classification accuracy comparable to state-of-the-art task-specific image classifiers. WND-CHARM can extract up to ~3,000 generic image descriptors (features) including polynomial decompositions, high contrast features, pixel statistics, and textures. These features are derived from the raw image, transforms of the image, and compound transforms of the image (transforms of transforms). The features are filtered and weighted depending on their effectiveness in discriminating between a set of predefined image classes (the training set). These features are then used to classify test images based on their similarity to the training classes. This classifier was tested on a wide variety of imaging problems including biological and medical image classification using several imaging modalities, face recognition, and other pattern recognition tasks.

To learn more about, and download WND-CHARM for use, click here.

XYT Event Detector detects and analyses time-dependent increases in intensity of a fluorescent indicator recorded by high-speed 2D cameras.  Specifically, the program was developed and tuned to detect Local Calcium Releases in cardiac pacemaker cells. It works with stacks of tif images of Ca signals measured in living cells. The consecutive images in the stack represent the intensity of local Ca dynamics measured with a fixed sampling rate by a high-speed camera and a fluorescent Ca indicator. When pacemaker cells generate a cardiac impulse, the action potential induces a global Ca increase in cytoplasmic Ca (dubbed AP-induced Ca transient). The program identifies and eliminates global signal shifts and transients and detects only local signals. Read more about the XYT Event Detector.