T. Hartonen

T. Hartonen
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T. Hartonen
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Physics - Physics and Society (2)
 
High Energy Physics - Phenomenology (1)
 
High Energy Physics - Experiment (1)
 
Physics - General Physics (1)
 
Computer Science - Digital Libraries (1)
 
Physics - Data Analysis; Statistics and Probability (1)
 
Quantitative Biology - Quantitative Methods (1)
 
Physics - Computational Physics (1)

Publications Authored By T. Hartonen

Direct-Coupling Analysis is a group of methods to harvest information about coevolving residues in a protein family by learning a generative model in an exponential family from data. In protein families of realistic size, this learning can only be done approximately, and there is a trade-off between inference precision and computational speed. We here show that an earlier introduced $l_2$-regularized pseudolikelihood maximization method called plmDCA can be modified as to be easily parallelizable, as well as inherently faster on a single processor, at negligible difference in accuracy. Read More

The advancement of various fields of science depends on the actions of individual scientists via the peer review process. The referees' work patterns and stochastic nature of decision making both relate to the particular features of refereeing and to the universal aspects of human behavior. Here, we show that the time a referee takes to write a report on a scientific manuscript depends on the final verdict. Read More

Cellular phones are now offering an ubiquitous means for scientists to observe life: how people act, move and respond to external influences. They can be utilized as measurement devices of individual persons and for groups of people of the social context and the related interactions. The picture of human life that emerges shows complexity, which is manifested in such data in properties of the spatiotemporal tracks of individuals. Read More

Scale-free and non-computable characteristics of natural networks are found to result from the least-time dispersal of energy. To consider a network as a thermodynamic system is motivated since ultimately everything that exists can be expressed in terms of energy. According to the variational principle, the network will grow and restructure when flows of energy diminish energy differences between nodes as well as relative to nodes in surrounding systems. Read More