Helsinki Institute for Information Technology

About: Helsinki Institute for Information Technology is a facility organization based out in Espoo, Finland. It is known for research contribution in the topics: Population & Bayesian network. The organization has 630 authors who have published 1962 publications receiving 63426 citations.

Predicting recognition between T cell receptors and epitopes with TCRGP

Abstract: Adaptive immune system uses T cell receptors (TCRs) to recognize pathogens and to consequently initiate immune responses. TCRs can be sequenced from individuals and methods analyzing the specificity of the TCRs can help us better understand individuals' immune status in different disorders. For this task, we have developed TCRGP, a novel Gaussian process method that predicts if TCRs recognize specified epitopes. TCRGP can utilize the amino acid sequences of the complementarity determining regions (CDRs) from TCRα and TCRβ chains and learn which CDRs are important in recognizing different epitopes. Our comprehensive evaluation with epitope-specific TCR sequencing data shows that TCRGP achieves on average higher prediction accuracy in terms of AUROC score than existing state-of-the-art methods in epitope-specificity predictions. We also propose a novel analysis approach for combined single-cell RNA and TCRαβ (scRNA+TCRαβ) sequencing data by quantifying epitope-specific TCRs with TCRGP and identify HBV-epitope specific T cells and their transcriptomic states in hepatocellular carcinoma patients.

Multi-touch pinch gestures: performance and ergonomics

Abstract: Multi-touch gestures are prevalent interaction techniques for many different types of devices and applications. One of the most common gestures is the pinch gesture, which involves the expansion or contraction of a finger spread. There are multiple uses for this gesture--zooming and scaling being the most common--but little is known about the factors affecting performance and ergonomics of the gesture motion itself. In this note, we present the results from a study where we manipulated angle, direction, distance, and position of two-finger pinch gestures. The study provides insight into how variables interact with each other to affect performance and how certain combinations of pinch gesture characteristics can result in uncomfortable or difficult pinch gestures. Our results can help designers select faster pinch gestures and avoid difficult pinch tasks.

Designing interactions for navigation in 3D mobile maps

Abstract: Due to their intuitiveness, 3D mobile maps have recently emerged as an alternative to 2D mobile maps. However, designing interactions for navigation in a 3D environment using a mobile device is non-trivial. Challenges are posed by the severe limitations of the mobile user interface and of the capacities of the mobile user. This chapter analyses the problem of degrees of freedom: how to make navigation quicker and more intuitive by the means of restricting and guiding movement, yet enabling unrestricted access to all reasonable points-of-interests. Insights from empirical studies of mobile map interaction are presented, in the form of a model of interactive search, to draw requirements for interaction design. Then, the design of controls, landmarks, cameras, interest fields, routes, paths etc. are analysed and several higher-level navigation metaphors are discussed. We propose ways to support spatial updating, rapid alignment of physical and virtual spaces, and overcoming the keyhole problem. A working prototype system is used to illustrate different solutions alongside with alternative designs, weighing their pros and cons.

Profiling persistent tubercule bacilli from patient sputa during therapy predicts early drug efficacy

Abstract: New treatment options are needed to maintain and improve therapy for tuberculosis, which caused the death of 1.5 million people in 2013 despite potential for an 86 % treatment success rate. A greater understanding of Mycobacterium tuberculosis (M.tb) bacilli that persist through drug therapy will aid drug development programs. Predictive biomarkers for treatment efficacy are also a research priority. Genome-wide transcriptional profiling was used to map the mRNA signatures of M.tb from the sputa of 15 patients before and 3, 7 and 14 days after the start of standard regimen drug treatment. The mRNA profiles of bacilli through the first 2 weeks of therapy reflected drug activity at 3 days with transcriptional signatures at days 7 and 14 consistent with reduced M.tb metabolic activity similar to the profile of pre-chemotherapy bacilli. These results suggest that a pre-existing drug-tolerant M.tb population dominates sputum before and after early drug treatment, and that the mRNA signature at day 3 marks the killing of a drug-sensitive sub-population of bacilli. Modelling patient indices of disease severity with bacterial gene expression patterns demonstrated that both microbiological and clinical parameters were reflected in the divergent M.tb responses and provided evidence that factors such as bacterial load and disease pathology influence the host-pathogen interplay and the phenotypic state of bacilli. Transcriptional signatures were also defined that predicted measures of early treatment success (rate of decline in bacterial load over 3 days, TB test positivity at 2 months, and bacterial load at 2 months). This study defines the transcriptional signature of M.tb bacilli that have been expectorated in sputum after two weeks of drug therapy, characterizing the phenotypic state of bacilli that persist through treatment. We demonstrate that variability in clinical manifestations of disease are detectable in bacterial sputa signatures, and that the changing M.tb mRNA profiles 0–2 weeks into chemotherapy predict the efficacy of treatment 6 weeks later. These observations advocate assaying dynamic bacterial phenotypes through drug therapy as biomarkers for treatment success.