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Intrachromosomal regulation decay in breast cancer

Guillermo de Anda-Jáuregui

Guillermo de Anda-Jáuregui

Computational Genomics Division, National Institute of Genomic MedicineCiudad de Mexico, Mexico
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Anda-Jáuregui, Guillermo de
, 
Cristobal Fresno

Cristobal Fresno

Computational Genomics Division, National Institute of Genomic MedicineCiudad de Mexico, Mexico
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Fresno, Cristobal
, 
Diana García-Cortés

Diana García-Cortés

Computational Genomics Division, National Institute of Genomic MedicineCiudad de Mexico, Mexico
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García-Cortés, Diana
, 
Jesús Espinal Enríquez

Jesús Espinal Enríquez

  • Computational Genomics Division, National Institute of Genomic MedicineCiudad de Mexico, Mexico
  • Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de MéxicoCiudad de Mexico, Mexico
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Enríquez, Jesús Espinal
 and 
Enrique Hernández-Lemus

Enrique Hernández-Lemus

  • Computational Genomics Division, National Institute of Genomic MedicineCiudad de Mexico, Mexico
  • Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de MéxicoCiudad de Mexico, Mexico
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Hernández-Lemus, Enrique
  
Jun 28, 2019
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Article Category: Papers dedicated to the memory of Valetnin Afraymovich (1945-2018)
Published Online: Jun 28, 2019
Page range: 223 - 230
Received: Aug 13, 2018
Accepted: Nov 13, 2018
DOI: https://doi.org/10.2478/AMNS.2019.1.00020
Keywords
© 2019 Guillermo de Anda-Jáuregui et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Fig. 1

Gene–gene mutual information–distance distributions. Depicted are chromosomes 1, 10, and 18 (large, medium, and small sized).
Gene–gene mutual information–distance distributions. Depicted are chromosomes 1, 10, and 18 (large, medium, and small sized).

Fig. 2

Model validation. A heatmap depicting Z-scored relative likelihood – as measured by adjusted coefficient of determination R2 – for the four models. Rows correspond to chromosomes, while columns correspond to the four models for nonscaled distance. Green tones correspond to low-to-negative scores, while the dark and red colours represent positive-to-high scores.
Model validation. A heatmap depicting Z-scored relative likelihood – as measured by adjusted coefficient of determination R2 – for the four models. Rows correspond to chromosomes, while columns correspond to the four models for nonscaled distance. Green tones correspond to low-to-negative scores, while the dark and red colours represent positive-to-high scores.
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