Bio
Anthony Baptista is a Postdoctoral Research Assistant in the group Complex Systems & Networks at the Queen Mary University of London (QMUL) and the Alan Turing Institute. He is involved in the project "Learning from data with structured missingness" which is part of the Turing-Roche partnership. He will closely work with Prof. Dr. Ginestra Bianconi (QMUL) and Dr. Ruben Sanchez-Garcia (University of Southampton), and all the people engaged in the project at the Alan Turing Institute.
Research interests
During his PhD, he worked on network theory, especially on the development of new multilayer network exploration methods to study biological networks. The methods developed were closely related to the integrated exploration of large multidimensional datasets that remain a major challenge in many scientific fields. In this context, he developed a new mathematical framework based on random walk with restart algorithm which is currently used for exploring the whole topology of large-scale networks. He also applied this kind of method to several biological questions such as the prioritization of gene and drug candidates involved in different disorders, gene-disease association predictions, and the integration of 3D DNA conformation information with gene and disease networks. During his Ph.D., he was also interested in the extension of several other methods to multilayer networks. In particular, the generalization of the Katz similarity measure to multilayer networks. He also developed a new method of community detection. Finally, he studied network embedding, especially in the case of shallow embedding methods.
Before his PhD he worked on the statistical physics of liquids. These works aimed to predict both theoretically with higher-order correlation functions and numerically with molecular dynamics simulation, the complex behavior of water and alcohol mixtures.
In conclusion, he is interested in a wide variety of subjects from Statistical Physics to Systems Biology. He is more than happy to be contacted to exchange and talk about science, especially around interdisciplinary topics.