Results 51 to 60 of about 7,625,750 (291)
Analysis of large-scale gene expression data
Briefings in Bioinformatics, 2000 The advent of cDNA and oligonucleotide microarray technologies has led to a paradigm shift in biological investigation, such that the bottleneck in research is shifting from data generation to data analysis. Hierarchical clustering, divisive clustering, self-organizing maps and k-means clustering have all been recently used to make sense of this mass ...
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Algorithmic and Statistical Perspectives on Large-Scale Data Analysis [PDF]
, 2010 In recent years, ideas from statistics and scientific computing have begun to interact in increasingly sophisticated and fruitful ways with ideas from computer science and the theory of algorithms to aid in the development of improved worst-case ...
Mahoney, Michael W.
core
Optimal Moments for the Analysis of Peculiar Velocity Surveys [PDF]
, 2001 We present a new method for the analysis of peculiar velocity surveys which removes contributions to velocities from small scale, nonlinear velocity modes while retaining information about large scale motions.
Adrian L. Melott +6 more
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Pediatric Blood &Cancer, EarlyView.Abstract Background Sickle cell disease (SCD) is an autosomal recessive hemoglobinopathy affecting millions of individuals worldwide. The clinical expression and psychosocial burden of SCD vary widely across geographical, cultural, and healthcare system contexts, underscoring the need for setting‐specific approaches to assessment.
Desiré Fantasia +7 more
wiley +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Chemotherapy‐induced peripheral neuropathy remains a major complication in pediatric cancer, with disrupted somatosensory and nociceptive processing being a key aspect. This review synthesizes empirical studies on alterations in somatosensory and nociceptive processing in children and adolescents with cancer.
Julia Schweiger +4 more
wiley +1 more source
Realtime Analysis of Large-Scale Data
, 2017 In photon science more and more data are taken. It is not possible anymore to store and process all data offline. In this book, we explore strategies for handling this large amount of data. A neural network as well as techniques from image processing are used to efficiently categorize and select useful data.
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Optimization of Large Scale HEP Data Analysis in LHCb
Journal of Physics: Conference Series, 2011 Observation has lead to a conclusion that the physics analysis jobs run by LHCb physicists on a local computing farm (i.e. non-grid) require more efficient access to the data which resides on the Grid. Our experiments have shown that the I/O bound nature of the analysis jobs in combination with the latency due to the remote access protocols (e.g. rfio,
Remenska, Daniela +5 more
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Approximation Algorithms for Large Scale Data Analysis [PDF]
Proceedings of the 40th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems, 2021 One of the greatest successes of computational complexity theory is the classification of countless fundamental computational problems into polynomial-time and NP-hard ones, two classes that are often referred to as tractable and intractable, respectively.
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, 2018 Apache Spark is a popular system aimed at the analysis of large data sets, but recent studies have shown that certain computations---in particular, many linear algebra computations that are the basis for solving common machine learning problems---are ...
Gerhardt, Lisa +8 more
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Large scale movement analysis from WiFi based location data [PDF]
, 2012 Understanding and modeling the way humans move in urban contexts is beneficial for many applications. The recent advances on positioning technologies, namely those based on the ubiquity of wireless networks, is facilitating the observation of people for ...
Meneses, Filipe, Moreira, Adriano
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