50,750 research outputs found
Common and Distinct Components in Data Fusion
In many areas of science multiple sets of data are collected pertaining to
the same system. Examples are food products which are characterized by
different sets of variables, bio-processes which are on-line sampled with
different instruments, or biological systems of which different genomics
measurements are obtained. Data fusion is concerned with analyzing such sets of
data simultaneously to arrive at a global view of the system under study. One
of the upcoming areas of data fusion is exploring whether the data sets have
something in common or not. This gives insight into common and distinct
variation in each data set, thereby facilitating understanding the
relationships between the data sets. Unfortunately, research on methods to
distinguish common and distinct components is fragmented, both in terminology
as well as in methods: there is no common ground which hampers comparing
methods and understanding their relative merits. This paper provides a unifying
framework for this subfield of data fusion by using rigorous arguments from
linear algebra. The most frequently used methods for distinguishing common and
distinct components are explained in this framework and some practical examples
are given of these methods in the areas of (medical) biology and food science.Comment: 50 pages, 12 figure
Essential guidelines for computational method benchmarking
In computational biology and other sciences, researchers are frequently faced
with a choice between several computational methods for performing data
analyses. Benchmarking studies aim to rigorously compare the performance of
different methods using well-characterized benchmark datasets, to determine the
strengths of each method or to provide recommendations regarding suitable
choices of methods for an analysis. However, benchmarking studies must be
carefully designed and implemented to provide accurate, unbiased, and
informative results. Here, we summarize key practical guidelines and
recommendations for performing high-quality benchmarking analyses, based on our
experiences in computational biology.Comment: Minor update
Scientific iconoclasm and active imagination: synthetic cells as techo-schientific mandalas
Metaphors allow us to come to terms with abstract and complex information, by comparing it to something which is structured, familiar and concrete. Although modern science is “iconoclastic”, as Gaston Bachelard phrases it, scientists are at the same time prolific producers of metaphoric images themselves. Synthetic biology is an outstanding example of a technoscientific discourse replete with metaphors, including textual metaphors such as the “Morse code” of life, the “barcode” of life and the “book” of life. This paper focuses on a different type of metaphor, however, namely on the archetypal metaphor of the mandala as a symbol of restored unity and wholeness. Notably, mandala images emerge in textual materials related to one of the new “frontiers” of contemporary technoscience, namely the building of a synthetic cell: a laboratory artefact that functions like a cell and is even able to replicate itself. The mandala symbol suggests that, after living systems have been successfully reduced to the elementary building blocks and barcodes of life, the time has now come to put these fragments together again. We can only claim to understand life, synthetic cell experts argue, if we are able to technically reproduce a fully functioning cell. This holistic turn towards the cell as a meaningful whole also requires convergence at the “subject pole”: the building of a synthetic cell as a practice of the self, representing a turn towards integration, of multiple perspectives and various forms of expertise
Toward a systems understanding of plant–microbe interactions
Plants are closely associated with microorganisms including pathogens and mutualists that influence plant fitness. Molecular genetic approaches have uncovered a number of signaling components from both plants and microbes and their mode of actions. However, signaling pathways are highly interconnected and influenced by diverse sets of environmental factors. Therefore, it is important to have systems views in order to understand the true nature of plant–microbe interactions. Indeed, systems biology approaches have revealed previously overlooked or misinterpreted properties of the plant immune signaling network. Experimental reconstruction of biological networks using exhaustive combinatorial perturbations is particularly powerful to elucidate network structure and properties and relationships among network components. Recent advances in metagenomics of microbial communities associated with plants further point to the importance of systems approaches and open a research area of microbial community reconstruction. In this review, we highlight the importance of a systems understanding of plant–microbe interactions, with a special emphasis on reconstruction strategies
Omnipresent Maxwell’s demons orchestrate information management in living cells
The development of synthetic biology calls for accurate
understanding of the critical functions that allow
construction and operation of a living cell. Besides
coding for ubiquitous structures, minimal genomes
encode a wealth of functions that dissipate energy in
an unanticipated way. Analysis of these functions
shows that they are meant to manage information
under conditions when discrimination of substrates
in a noisy background is preferred over a simple
recognition process. We show here that many of
these functions, including transporters and the ribosome
construction machinery, behave as would
behave a material implementation of the informationmanaging
agent theorized by Maxwell almost
150 years ago and commonly known as Maxwell’s
demon (MxD). A core gene set encoding these functions belongs to the minimal genome required
to allow the construction of an autonomous cell.
These MxDs allow the cell to perform computations
in an energy-efficient way that is vastly better than
our contemporary computers
Grid Added Value to Address Malaria
Through this paper, we call for a distributed, internet-based collaboration
to address one of the worst plagues of our present world, malaria. The spirit
is a non-proprietary peer-production of information-embedding goods. And we
propose to use the grid technology to enable such a world wide "open source"
like collaboration. The first step towards this vision has been achieved during
the summer on the EGEE grid infrastructure where 46 million ligands were docked
for a total amount of 80 CPU years in 6 weeks in the quest for new drugs.Comment: 7 pages, 1 figure, 6th IEEE International Symposium on Cluster
Computing and the Grid, Singapore, 16-19 may 2006, to appear in the
proceeding
Literature-based discovery of diabetes- and ROS-related targets
Abstract Background Reactive oxygen species (ROS) are known mediators of cellular damage in multiple diseases including diabetic complications. Despite its importance, no comprehensive database is currently available for the genes associated with ROS. Methods We present ROS- and diabetes-related targets (genes/proteins) collected from the biomedical literature through a text mining technology. A web-based literature mining tool, SciMiner, was applied to 1,154 biomedical papers indexed with diabetes and ROS by PubMed to identify relevant targets. Over-represented targets in the ROS-diabetes literature were obtained through comparisons against randomly selected literature. The expression levels of nine genes, selected from the top ranked ROS-diabetes set, were measured in the dorsal root ganglia (DRG) of diabetic and non-diabetic DBA/2J mice in order to evaluate the biological relevance of literature-derived targets in the pathogenesis of diabetic neuropathy. Results SciMiner identified 1,026 ROS- and diabetes-related targets from the 1,154 biomedical papers (http://jdrf.neurology.med.umich.edu/ROSDiabetes/). Fifty-three targets were significantly over-represented in the ROS-diabetes literature compared to randomly selected literature. These over-represented targets included well-known members of the oxidative stress response including catalase, the NADPH oxidase family, and the superoxide dismutase family of proteins. Eight of the nine selected genes exhibited significant differential expression between diabetic and non-diabetic mice. For six genes, the direction of expression change in diabetes paralleled enhanced oxidative stress in the DRG. Conclusions Literature mining compiled ROS-diabetes related targets from the biomedical literature and led us to evaluate the biological relevance of selected targets in the pathogenesis of diabetic neuropathy.http://deepblue.lib.umich.edu/bitstream/2027.42/78315/1/1755-8794-3-49.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/2/1755-8794-3-49-S7.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/3/1755-8794-3-49-S10.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/4/1755-8794-3-49-S8.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/5/1755-8794-3-49-S3.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/6/1755-8794-3-49-S1.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/7/1755-8794-3-49-S4.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/8/1755-8794-3-49-S2.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/9/1755-8794-3-49-S12.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/10/1755-8794-3-49-S11.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/11/1755-8794-3-49-S9.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/12/1755-8794-3-49-S5.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/13/1755-8794-3-49-S6.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/14/1755-8794-3-49.pdfPeer Reviewe
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