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Epilogue: The road ahead
Published in Karthik Raman, An Introduction to Computational Systems Biology, 2021
Students, from across different years, and disciplines, have unanimously emphasised to me the value of lab sessions3, and a seven-week long course project in honing their skills and improve their understanding of a variety of concepts covered in this course. This project, which I usually ask students to carry out in pairs, requires students to carry out a research project in the area of mathematical modelling of any biological system. I often try to pair up students in such a way that their biology and programming knowledge/skills are complementary, to the extent possible. This bringing together of ‘unlike’ minds fosters creativity, and the spirit of collaboration, which is indispensable for modern research, particularly in emergent interdisciplinary areas such as computational systems biology.
Linear Algebra in Biomolecular Modeling
Published in Leslie Hogben, Richard Brualdi, Anne Greenbaum, Roy Mathias, Handbook of Linear Algebra, 2006
As in all other types of scientific computing, linear algebra is one of the most powerful mathematical tools for biological computing. Here we review several subjects in biomolecular modeling, where linear algebra has played a major role, including mapping from distances to coordinates in NMR structure determination (Section 60.2), solving the Procrustes problem for structural comparison (Section 60.3), exploiting the structure of the Karle–Hauptman matrix in protein x-ray crystallography (Section 60.4), computing the fast and slow modes of protein motions (Section 60.5), and solving the flux balancing equations in metabolic network simulation (Section 60.6). The last subject actually involves the modeling of a large biological system, something beyond conventional biomolecular modeling, yet of increased research interests in computational systems biology [Kit99].
Cancer
Published in Inna Kuperstein, Emmanuel Barillot, Computational Systems Biology Approaches in Cancer Research, 2019
Inna Kuperstein, Emmanuel Barillot
The book is written in co-authorship with the leading specialists from different fields in cancer systems biology. It consists of six thematic chapters each dedicated to a different domain across computational systems biology approaches in cancer. It is structured with the idea to trigger the reader’s interest and to provide references and links for immediate and easy exploitation of suggested methods.
Development of a database on key characteristics of human carcinogens
Published in Journal of Toxicology and Environmental Health, Part B, 2019
Mustafa Al-Zoughool, Michael Bird, Jerry Rice, Robert A. Baan, Mélissa Billard, Nicholas Birkett, Daniel Krewski, Jan M Zielinski
Early descriptors of the mode of action of carcinogens were often based upon assays of ‘gross’ cytogenetic events including DNA strand-breakage and formation of micronuclei (MN) and chromosomal aberrations (CA). Most of the early mechanistic studies focused on the ability of agents to induce genotoxic effects. Recent advances in molecular and cell biology have elucidated the critical role of a number of cellular and molecular processes and pathways – including transcription factors, signaling molecules, and epigenetic events – involved in chemical-mediated carcinogenesis. In parallel with breakthroughs in molecular biology, advances in applying high-throughput microarrays, toxicogenomics, and computational systems-biology have also increased our understanding of mechanisms underlying cancer occurrence (Krewski et al. 2011).