662,884 research outputs found
Mobile support in CSCW applications and groupware development frameworks
Computer Supported Cooperative Work (CSCW) is an established subset of the field of Human Computer Interaction that deals with the how people use computing technology to enhance group interaction and collaboration. Mobile CSCW has emerged as a result of the progression from personal desktop computing to the mobile device platforms that are ubiquitous today.
CSCW aims to not only connect people and facilitate communication through using computers; it aims to provide conceptual models coupled with technology to manage, mediate, and assist collaborative processes. Mobile CSCW research looks to fulfil these aims through the adoption of mobile technology and consideration for the mobile user. Facilitating collaboration using mobile devices brings new challenges. Some of these challenges are inherent to the nature of the device hardware, while others focus on the understanding of how to engineer software to maximize effectiveness for the end-users. This paper reviews seminal and state-of-the-art cooperative software applications and development frameworks, and their support for mobile devices
Common dysregulation network in the human prefrontal cortex underlies two neurodegenerative diseases.
Using expression profiles from postmortem prefrontal cortex samples of 624 dementia patients and non-demented controls, we investigated global disruptions in the co-regulation of genes in two neurodegenerative diseases, late-onset Alzheimer's disease (AD) and Huntington's disease (HD). We identified networks of differentially co-expressed (DC) gene pairs that either gained or lost correlation in disease cases relative to the control group, with the former dominant for both AD and HD and both patterns replicating in independent human cohorts of AD and aging. When aligning networks of DC patterns and physical interactions, we identified a 242-gene subnetwork enriched for independent AD/HD signatures. This subnetwork revealed a surprising dichotomy of gained/lost correlations among two inter-connected processes, chromatin organization and neural differentiation, and included DNA methyltransferases, DNMT1 and DNMT3A, of which we predicted the former but not latter as a key regulator. To validate the inter-connection of these two processes and our key regulator prediction, we generated two brain-specific knockout (KO) mice and show that Dnmt1 KO signature significantly overlaps with the subnetwork (P = 3.1 Ă— 10(-12)), while Dnmt3a KO signature does not (P = 0.017)
Sparse multi-view matrix factorisation: a multivariate approach to multiple tissue comparisons
Gene expression levels in a population vary extensively across tissues. Such
heterogeneity is caused by genetic variability and environmental factors, and
is expected to be linked to disease development. The abundance of experimental
data now enables the identification of features of gene expression profiles
that are shared across tissues, and those that are tissue-specific. While most
current research is concerned with characterising differential expression by
comparing mean expression profiles across tissues, it is also believed that a
significant difference in a gene expression's variance across tissues may also
be associated to molecular mechanisms that are important for tissue development
and function. We propose a sparse multi-view matrix factorisation (sMVMF)
algorithm to jointly analyse gene expression measurements in multiple tissues,
where each tissue provides a different "view" of the underlying organism. The
proposed methodology can be interpreted as an extension of principal component
analysis in that it provides the means to decompose the total sample variance
in each tissue into the sum of two components: one capturing the variance that
is shared across tissues, and one isolating the tissue-specific variances.
sMVMF has been used to jointly model mRNA expression profiles in three tissues
- adipose, skin and LCL - which are available for a large and well-phenotyped
twins cohort, TwinsUK. Using sMVMF, we are able to prioritise genes based on
whether their variation patterns are specific to each tissue. Furthermore,
using DNA methylation profiles available, we provide supporting evidence that
adipose-specific gene expression patterns may be driven by epigenetic effects.Comment: in Bioinformatics 201
Comprehensive structural classification of ligand binding motifs in proteins
Comprehensive knowledge of protein-ligand interactions should provide a
useful basis for annotating protein functions, studying protein evolution,
engineering enzymatic activity, and designing drugs. To investigate the
diversity and universality of ligand binding sites in protein structures, we
conducted the all-against-all atomic-level structural comparison of over
180,000 ligand binding sites found in all the known structures in the Protein
Data Bank by using a recently developed database search and alignment
algorithm. By applying a hybrid top-down-bottom-up clustering analysis to the
comparison results, we determined approximately 3000 well-defined structural
motifs of ligand binding sites. Apart from a handful of exceptions, most
structural motifs were found to be confined within single families or
superfamilies, and to be associated with particular ligands. Furthermore, we
analyzed the components of the similarity network and enumerated more than 4000
pairs of ligand binding sites that were shared across different protein folds.Comment: 13 pages, 8 figure
- …