FaST-LMM (Factored Spectrally Transformed Linear Mixed Models) is a set of tools for performing genome-wide association studies (GWAS) on large data sets. FaST-LMM runs on both Windows and Linux, and contains code to do (1) univariate GWAS, (2) testing sets of SNPs, (3) feature selection for background correction, (4) epistatic association scans, (5) a correction method for cellular heterogeneity in methylation and similar data.
We are looking for participants to engage in a personalised online shopping experience. You will receive a £40 shopping voucher for your participation and get the opportunity to purchase a book at 90% discount. The experiment involves a session of online shopping during which we will measure your eye movements and bodily responses. The shopping session is followed by an interview and we will ask you to fill out a final questionnaire to give us feedback on the study.
The global hub for sustainable development at Microsoft Research
GeoS is a Windows application for interactive semi automated segmentation of medical images such as CT (Computed Tomography) and MR (Magnetic Resonance) scans.
Microsoft Research is looking for parents of children with a chronic health condition to fill out a 10-minute survey with questions on how their child stays in touch with friends when they are away from friends because of various factors from their illness. In addition, they also ask that the child fill out a 10-minute survey on their experiences of staying in touch with their friends.
This project focuses on rural government maternal health workers in India (called Accredited Social Health Activists, or ASHAs), using a tool called ASHA Assist to help ASHAs engage their clients in persuasive discussions about various topics related to maternal health. ASHA Assist consists of interactive videos on mobile phones, covering topics related to maternal health for use in counseling their clients.
In recent years the Web has evolved substantially, transforming from a place where we primarily find information to a place where we also leave, share and keep it. This presents a fresh set of challenges for the management of personal information, which include how to underpin greater awareness and more control over digital belongings and other personally meaningful content that is hosted online.
An increased dependence on medical imaging for patient diagnosis and treatment places new challenges upon the clinical community. Existing image processing workflows struggle to keep up with the pace at which imaging technology is developing. Microsoft Research is working with top research institutes around the world to make available data and tools and advance the state of the art in automatic analysis of medical scans.
Microsoft Research Connections partnered with the University of Southern California Annenberg Innovation Lab, Brown University, University of Iowa Digital Studio for Public Humanities, National Endowment for the Humanities, NAMES Project Foundation, and others to create several interactive digital exhibits that allow the public to explore the largest work of community-created folk art in the world.
We present AffectAura, an emotional prosthetic that allows users to reflect on their emotional states over long periods of time. We designed a multimodal sensor set-up for continuous logging of audio, visual, physiological and contextual data, a classification scheme for predicting user affective state and an interface for user reflection. The system continuously predicts a user's valence, arousal and engagement, and correlates this with information on events, communications and data i
Using analysis of social media posts, we look for linguistic markers that might indicate postpartum depression.
People are increasingly conscious of their everyday health and wellness conditions, and actively seek to improve them. In this project, we build software and hardware solutions that utilize and/or augment mobile phones to continuously monitor users' wellness without changing their existing lifestyle. Instead of solely passive monitoring, we further explore the actuation possibilities, i.e., seek to leverage the social networks to properly motivate the user towards improved health conditions.
In recent years, computational challenges have become more and more important to infer biologically relevant information from the vast amount of experimental data available to systems biologists.
Labs: New England
This project explores the use of new touchless technology in medical practice.
eHuatuo is an eHealthcare project about Teaching Computer to Read Medical Records developed by Microsoft Research Asia. The goal of the project is to utilize the power of computers to help doctors process the increasing amount of data available in healthcare, ranging from text data, medical imaging data, to genomic data. We aim to link these disparate types of data together for new insights and discoveries.
Extraction of structured information from biomedical text.
Understanding the properties, challenges and social consequences of touchless body-based interactions
Electronic health records have the potential to vastly improve health care; however, they also introduce new and severe security and privacy concerns. We explore the challenge of preserving patients’ privacy in electronic health record systems.
We are working in collaboration with the Manchester Asthma and Allergy Study (MAAS) and Shared Genomics project to gain a better understanding of the genetic and environmental causes of childhood asthma. An important part of this work is to explore the phenotypes exhibited by children suffering from asthma, the underlying assumption being that asthma actually corresponds to a group of diseases with similar, but not identical, phenotypes.
The Microsoft Biology Initiative (MBI) is a Microsoft Research effort to bring new technology and tools to bioinformatics and biology research. This initiative is comprised of two primary components, .NET Bio (formerly Microsoft Biology Foundation [MBF]) and the Microsoft Biology Tools (MBT).
Immunodominance lies at the heart of the immune system's ability to distinguish self from non-self. Understanding and possibly controlling the mechanisms that govern immunodominance will have profound consequences for the fight against several classes of diseases, including viral infections and cancer. In the first phase of this project, we focus on computational modelling of MHC class I peptide editing.
This tool enables biologists and modelers to construct high-level theories and models of biological systems, capturing biological hypotheses, inferred mechanisms, and experimental results within the same framework. Among the key features of the tool are convenient ways to represent several competing theories and the interactive nature of building and running the models using an intuitive, rigorous scenario-based visual language.
If the idea of constructing family is one theme, then another is the converse: the idea that domestic spaces might be socially and technologically fractionated in ways that people desire. Hence research in this theme is looking at how ‘domestic’ or private settings may be constituted by connections to other places and people and in other cases by partitionings and separations of places and people.
Here research is examining how the ‘idea of family’ can be a sociological topic and a design orientation leading to technical innovation and new user experiences. Various research activities are seeking ways of capturing traces of family activity, assembling and creating new representations of these activities, as well as inventing new ways to interact with and display those traces.
The Stochastic Pi Machine (SPiM) is a programming language for designing and simulating computer models of biological processes. The language is based on a mathematical formalism known as the pi-calculus, and the simulation algorithm is based on standard kinetic theory of physical chemistry. The language features a simple graphical notation for modelling a range of biological systems, and can be used to model large systems incrementally, by directly composing simpler models of subsystems.