TY - GEN
T1 - Representation of Chromosome Conformations Using a Shape Alphabet Across Modeling Methods
AU - Soto, Carlos
AU - Dalgarno, Audrey
AU - Bryner, Darshan
AU - McLaughlin, Benjamin
AU - Neretti, Nicola
AU - Srivastava, Anuj
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - Despite enormous structural variability exhibited in 3D chromosomal conformations at a global scale, there is a significant commonality of structures visible at smaller, local levels. We hypothesize that chromosomal conformations are representable as concatenations of a handful of prototypical shapelets, termed shape letters. This is akin to expressing complicated sentences in a language using only a small set of letters. Our goal is to organize the vast variability of 3D chromosomal conformation by constructing a set of predominant shape letters, termed a shape alphabet, using statistical shape analysis of curvelets taken from training conformations. This paper utilizes conformations generated from Integrative Genome Modeling to develop a shape alphabet as follows: it first segments 3D conformations into curvelets according to their Topologically Associated Domains. It then clusters these segments, estimates mean shapes, and refines and reorders these shapes into a Chromosome Shape Alphabet. The paper demonstrates effectiveness of this construction by successfully representing independent test conformations taken from IGM and other methods such as SIMBA3D, both symbolically and structurally, using the constructed alphabet.
AB - Despite enormous structural variability exhibited in 3D chromosomal conformations at a global scale, there is a significant commonality of structures visible at smaller, local levels. We hypothesize that chromosomal conformations are representable as concatenations of a handful of prototypical shapelets, termed shape letters. This is akin to expressing complicated sentences in a language using only a small set of letters. Our goal is to organize the vast variability of 3D chromosomal conformation by constructing a set of predominant shape letters, termed a shape alphabet, using statistical shape analysis of curvelets taken from training conformations. This paper utilizes conformations generated from Integrative Genome Modeling to develop a shape alphabet as follows: it first segments 3D conformations into curvelets according to their Topologically Associated Domains. It then clusters these segments, estimates mean shapes, and refines and reorders these shapes into a Chromosome Shape Alphabet. The paper demonstrates effectiveness of this construction by successfully representing independent test conformations taken from IGM and other methods such as SIMBA3D, both symbolically and structurally, using the constructed alphabet.
UR - http://www.scopus.com/inward/record.url?scp=85125175616&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85125175616&partnerID=8YFLogxK
U2 - 10.1109/BIBM52615.2021.9669716
DO - 10.1109/BIBM52615.2021.9669716
M3 - Conference contribution
AN - SCOPUS:85125175616
T3 - Proceedings - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021
SP - 151
EP - 156
BT - Proceedings - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021
A2 - Huang, Yufei
A2 - Kurgan, Lukasz
A2 - Luo, Feng
A2 - Hu, Xiaohua Tony
A2 - Chen, Yidong
A2 - Dougherty, Edward
A2 - Kloczkowski, Andrzej
A2 - Li, Yaohang
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021
Y2 - 9 December 2021 through 12 December 2021
ER -