Section 1 - Cancer systems biology: An overview
1: Sui Huang: The necessary existence of cancer and its progression from first principles of cell state dynamics
2: Vera Pancaldi and Jean- Pascal Capp: Non- genetic intratumoral heterogeneity and phenotypic plasticity as consequences of microenvironment- driven epigenomic dysregulation
3: Caterina A.M. La Porta and Stefano Zapperi: Dimensions of cellular plasticity: EpithelialDS mesenchymal transition, cancer stem cells, and collective cell migration
4: Divyjoy Singh, Abhay Gupta, Mohit Kumar Jolly, and Prakash Kulkarni: Phenotypic switching in cancer: A systems- level perspective
5: Biplab Bose: Morphological state transition during epithelialDS mesenchymal transition
Section 2 - Cancer systems biology: New paradigms
6: Laurie Graves, Ayalur Raghu Subbalakshmi, William C. Eward, Mohit Kumar Jolly, and Jason A. Somarelli: Evolution- informed multilayer networks: Overlaying comparative evolutionary genomics with systems- level analyses for cancer drug discovery
7: Jintong Lang, Chunhe Li, and Jinzhi Lei: Landscape of cell- fate decisions in cancer cell plasticity
8: Arnab Barua and Haralampos Hatzikirou: The road to cancer and back: A thermodynamic point of view
9: Paromita Mitra, Uday Saha, Subhashis Ghosh, and Sandeep Singh: Cellular plasticity as emerging target against dynamic complexity in cancer
10: Vishaka Gopalan, Sidhartha Goyal, and Sumaiyah Rehman: Modeling phenotypic heterogeneity and cell- state transitions during cancer progression
Section 3 - Single cell 'omics' analysis
11: Benedict Anchang and Loukia G. Karacosta: Decoding drug resistance at a single- cell level using systems- level approaches
12: Manu Setty: Computational methods to infer lineage decision- making in cancer using single-cell data
13: Jianhua Xing and Weikang Wang: Analyzing cancer cell- state transition dynamics through live- cell imaging and high- dimensional single-cell trajectory analyses
14: Syeda Subia Ahmed, Danielle Pi, Nicholas Bodkin, Vito W. Rebecca, and Yogesh Goyal: Emerging single- cell technologies and concepts to trace cancer progression and drug resistance
Section 4 - Computational approaches to drug development
15: Supriyo Bhattacharya: Navigating protein dynamics: Bridging the gap with deep learning and machine intelligence
16: Vitor B.P. Leite, Murilo N. Sanches, and Rafael G. Viegas: Cancer- related intrinsically disordered proteins: Functional insights from energy landscape analysis
17: Priyanka Prakash: Targeting RAS
Section 5 - Statistical methods and data mining, machine learning, artificial intelligence, and cloud computing
18: Brandi N. Davis- Dusenbery, Cera R. Fisher, Rowan Beck, and Zelia F. Worman: The power of connectionDLenabling collaborative, multimodal data analysis at petabyte scale to advance understanding of oncology
19: Colton Ladbury and Arya Amini: Interpretation of machine learning models in cancer: The role of model- agnostic explainable artificial intelligence
20: Jay G. Ronquillo: Applying cloud computing and informatics in cancer
21: Luciane T. Kagohara and Joseph Tandurella: Single-cell sequencing analysis focused on cancer immunotherapy
22: Arnulf Stenzl, Jenny Ghith, and Bob J.A. Schijvenaars: Application of artificial intelligence to overcome clinical information overload in cancer
23: Xiwei Wu and Supriyo Bhattacharya: Application of artificial intelligence in cancer genomics
Section 6 - Biomechanics
24: Madhurima Sarkar, Asadullah, and Shamik Sen: A role for mechanical heterogeneity in the tumor microenvironment in driving cancer cell invasion
25: Christina R. Dollahon, Ting- Ching Wang, Srinikhil S. Vemuri, Suchitaa Sawhney, and Tanmay P. Lele: Adaptation of cancer cells to altered stiffness of the extra-cellular matrix
26: Ajay Tijore, Alka Kumari, and Abhishek Goswami: Decoding mechano- oncology principles through microfluidic devices and biomaterial platforms
27: Yasir Suhail, Wenqiang Du, Günter Wagner, and Kshitiz: Understanding contribution of fibroblasts in inception of cancer metastasis from an evolutionary perspective
28: Medhavi Vishwakarma and Amrapali Datta: Cell competition in tumorigenesis and epithelial defense against cancer
Section 7 - Translational mathematical oncology
29: Philipp M. Altrock, Guranda Chitadze, Arne Traulsen, and Frederick L. Locke: Modelling cell population dynamics during chimeric antigen receptor T- cell therapy
30: Srisairam Achuthan, Rishov Chatterjee, and Atish Mohanty: Modeling small cell lung cancer biology through deterministic and stochastic mathematical models
31: Jasmine Foo and Einar Bjarki Gunnarsson: Mathematical models of resistance evolution under continuous and pulsed anti- cancer therapies
32: Mohammad Kohandel, Cameron Meaney, and Dorsa Mohammadrezaei: Integrating in silico models with ex vivo data for designing better combinatorial therapies in cancer
33: Annice Najafi and Jason George: Tumour- immune co- evolution dynamics and it's impact on immuno- therapy optimization
34: Maria Jose Peláez, Shreya Goel, Vittorio Cristini, Zhihui Wang, and Prashant Dogra: Mechanistic modelling and machine learning to establish structureDS activity relationship of nanomaterials for improved tumour delivery
Section 8 - Ecology, evolution, and cancer
35: Rowan Barker- Clarke, Eshan S. King, Jeff Maltas, J. Arvid Ågren, Dagim Tadele, and Jacob G. Scott: Decoding cancer evolution through adaptive fitness landscapes
36: Andriy Marusyk: A case against causal reductionism in acquired therapy resistance
37: Ravi Salgia, Supriyo Bhattacharya, Atish Mohanty, and Govindan Rangarajan: Group behaviour and drug resistance in cancer
38: Jeffrey West, Jill Gallaher, Maximilian A.R. Strobl, Mark Robertson- Tessi, and Alexander R.A. Anderson: The Fundamentals of evolutionary therapy in cancer
Section 9 - Critical transitions and chaos in cancer
39: Smita Deb, Subhendu Bhandary, Mohit Kumar Jolly, and Partha Sharathi Dutta: Methods for identifying critical transitions during cancer progression
40: Abicumaran Uthamacumaran: Chaos and complexity: Hallmarks of cancer progression
41: Andrzej Kasperski and Henry H. Heng: Cancer formation as creation and penetration of unknown life spaces
