Analyzing deviation pattern in strongly-correlated genes through core cluster mining

2013 ◽  
Vol 251 ◽  
pp. 47-62 ◽  
Author(s):  
Ramkishore Bhattacharyya
1989 ◽  
Vol 54 (1) ◽  
pp. 101-105 ◽  
Author(s):  
J. Bruce Tomblin ◽  
Cynthia M. Shonrock ◽  
James C. Hardy

The extent to which the Minnesota Child Development Inventory (MCDI), could be used to estimate levels of language development in 2-year-old children was examined. Fifty-seven children between 23 and 28 months were given the Sequenced Inventory of Communication Development (SICD), and at the same time a parent completed the MCDI. In addition the mean length of utterance (MLU) was obtained for each child from a spontaneous speech sample. The MCDI Expressive Language scale was found to be a strong predictor of both the SICD Expressive scale and MLU. The MCDI Comprehension-Conceptual scale, presumably a receptive language measure, was moderately correlated with the SICD Receptive scale; however, it was also strongly correlated with the expressive measures. These results demonstrated that the Expressive Language scale of the MCDI was a valid predictor of expressive language for 2-year-old children. The MCDI Comprehension-Conceptual scale appeared to assess both receptive and expressive language, thus complicating its interpretation.


2019 ◽  
Author(s):  
Sam G. B. Roberts ◽  
Anna Roberts

Group size in primates is strongly correlated with brain size, but exactly what makes larger groups more ‘socially complex’ than smaller groups is still poorly understood. Chimpanzees (Pan troglodytes) and gorillas (Gorilla gorilla) are among our closest living relatives and are excellent model species to investigate patterns of sociality and social complexity in primates, and to inform models of human social evolution. The aim of this paper is to propose new research frameworks, particularly the use of social network analysis, to examine how social structure differs in small, medium and large groups of chimpanzees and gorillas, to explore what makes larger groups more socially complex than smaller groups. Given a fission-fusion system is likely to have characterised hominins, a comparison of the social complexity involved in fission-fusion and more stable social systems is likely to provide important new insights into human social evolution


2014 ◽  
Vol 59 (5) ◽  
pp. 487-494 ◽  
Author(s):  
I. Bariakhtar ◽  
◽  
A. Nazarenko ◽  
◽  
◽  
...  

2018 ◽  
Author(s):  
Shannon Houck ◽  
Nicholas Mayhall

<div>Many multiconfigurational systems, such as single-molecule magnets, are difficult to study using traditional computational methods due to the simultaneous existence of both spin and spatial degeneracies. In this work, a new approach termed n-spin-flip Ionization Potential/Electron Affinity (<i>n</i>SF-IP or <i>n</i>SF-EA) is introduced which combines the spin-flip method of Anna Krylov with particle-number changing IP/EA methods. We demonstrate the efficacy of the approach by applying it to the strongly-correlated N<sub>2</sub><sup>+</sup> as well as several double exchange systems. We also demonstrate that when these systems are well-described by a double exchange model Hamiltonian, only 1SF-IP/EA is required to extract the double exchange parameters and accurately predict energies for the low-spin states. This significantly reduces the computational effort for studying such systems. The effects of including additional excitations (using a RAS-<i>n</i>SF-IP/EA scheme) are also examined, with particular emphasis on hole and particle excitations.</div>


2018 ◽  
Author(s):  
Shannon Houck ◽  
Nicholas Mayhall

<div>Many multiconfigurational systems, such as single-molecule magnets, are difficult to study using traditional computational methods due to the simultaneous existence of both spin and spatial degeneracies. In this work, a new approach termed n-spin-flip Ionization Potential/Electron Affinity (<i>n</i>SF-IP or <i>n</i>SF-EA) is introduced which combines the spin-flip method of Anna Krylov with particle-number changing IP/EA methods. We demonstrate the efficacy of the approach by applying it to the strongly-correlated N<sub>2</sub><sup>+</sup> as well as several double exchange systems. We also demonstrate that when these systems are well-described by a double exchange model Hamiltonian, only 1SF-IP/EA is required to extract the double exchange parameters and accurately predict energies for the low-spin states. This significantly reduces the computational effort for studying such systems. The effects of including additional excitations (using a RAS-<i>n</i>SF-IP/EA scheme) are also examined, with particular emphasis on hole and particle excitations.</div>


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