Courses from 1000+ universities
Buried in Coursera’s 300-page prospectus: two failed merger attempts, competing bidders, a rogue shareholder, and a combined market cap that shrank from $3.8 billion to $1.7 billion.
600 Free Google Certifications
Bitcoin and Cryptocurrency Technologies
The Emergence of the Modern Middle East - Part I
Six Sigma Part 1: Define and Measure
Organize and share your learning with Class Central Lists.
View our Lists Showcase
Explore biological network dynamics and design, focusing on specific case studies. Gain insights into complex systems and their applications in theoretical approaches to cancer research.
Explore cutting-edge predictive models for single-cell and regulatory genomics, enhancing understanding of cancer progression and potential treatment approaches.
Explore AI applications in cancer detection and treatment, covering advanced techniques for early diagnosis, personalized therapies, and improved patient outcomes.
Comprehensive introduction to neural networks, covering fundamental concepts, architectures, and applications in machine learning and artificial intelligence.
Explore computational approaches to predict cell phenotypes from genomic data using biochemical network reconstruction, advancing our understanding of cellular behavior and disease mechanisms.
Explore systems analysis of temozolomide response in glioblastoma, uncovering insights into cancer treatment through advanced modeling and data interpretation techniques.
Explore morphogenesis in cancer with Ramray Bhat, examining fundamental principles and theoretical approaches to understanding cancer progression and potential treatment strategies.
Explore systems biology approaches to unravel cell cycle dynamics, focusing on mathematical modeling and computational techniques to understand complex cellular processes.
Explore structural and stochastic modeling techniques to analyze tumor-immune interactions, enhancing understanding of cancer dynamics and potential treatment strategies.
Explore mammalian cell cycle regulation modeling techniques, focusing on theoretical approaches to understand cancer progression and treatment. Gain insights into advanced mathematical and computational methods.
Explore spatial models of tumor growth in this lecture on mathematical oncology, examining theoretical approaches to understand cancer progression and treatment strategies.
Explore mathematical modeling in cancer research, covering population dynamics, systems biology, and machine learning to enhance understanding and treatment of this complex disease.
Explore opportunities and challenges in oncology drug development, focusing on mechanistic modeling approaches to enhance treatment strategies and overcome resistance.
Explore disease map modeling and analysis techniques for understanding complex biological systems and their applications in cancer research and treatment strategies.
Explore genome-scale metabolic modeling in cancer research, uncovering insights into cellular metabolism and potential therapeutic targets for improved cancer treatment strategies.
Get personalized course recommendations, track subjects and courses with reminders, and more.