First global analysis of human birth-rate cycles reveals that post-holiday ‘baby boom’ persists across cultures, hemispheres. CNetS PhD student Ian Wood and Professors Luis Rocha and Johan Bollen, in collaboration with Joana Sá, used data science and computational social science methods to demonstrate that “Human Sexual Cycles are Driven by Culture and Match Collective Moods.” See full article at IU News and media coverage in many venues such as The Independent, Time, Newsweek, Publico, ScienceDaily, Phys.org, The National Post, DailyMail, The Hindustan Times, Men’s Fitness, Mother Jones, Drive with Yasmeen Khan (at 17:30) (audio of interview), etc. Discussion of the paper was a top trending topic on Reddit. Watch a short video about the research.
“On the last Friday of each month, instead of heading home to their families after the weekly School of Informatics, Computing and Engineering faculty meeting, professors Luis Rocha and Johan Bollen head to the Root Cellar Lounge and become DJ E-Trash and DJ Angst. […] Both Bollen and Rocha are considered experts in the field of complex networks and systems, and they agree that when they DJ, they are part of just the kind of complex systems they study”. See full article at IU News.
The National Science Foundation has awarded nearly $3 million to train future research leaders in Complex Networks and Systems, via the PhD Program established by CNETS faculty. The highly selective grant from the NSF’s Research Traineeship Award will create a dual Ph.D. program at Indiana University to train graduate students to be proficient in both a specific discipline, such as psychology or political science, as well as network, complexity and data science. The new Ph.D. program will also leverage the strengths of the Indiana Network Science Institute, or IUNI, to involve students in interdisciplinary research.”The biggest challenges currently faced by society require large teams of people who are ‘fluent’ in more than one scientific discipline,” said Luis Rocha, CNETS professor in the IU School of Informatics, Computing, and Engineering who will lead the new program. “But the current education model in academia is still largely focused on training researchers who know how to set up independent labs with agendas driven by a single person. If we want to take on the really big problems, we’ve got to create more scientists with deep expertise in multiple areas.” Full Press Release Available.
‘Musical Morphogenesis’ is an interactive installation that translates to sound, movement and lights the dynamics behind the development of petals in a flower. It is a collaborative piece developed by designers, architects, musicians and scientists in Luis Rocha‘s CASCI group. The control of this robotic “macroscope” is an implementation of the gene regulatory network of the Thaliana Arabidopsis flower. The installation provides a sensorial exploration of the dynamics between genes and proteins that leads to organ formation in plants, namely sepals, stamen, and petals. The genetic network provides an interactive “genetic soundtrack” that allows visitors to control the development of the plant towards its wild-type or mutant states. The installation has been on display at various museums such as the Science Museum in Lisbon, Gulbenkian Foundation, and the Belém ArtFest. This week it will be displayed at Dia D Ligações – Gulbenkian Foundation.
Sponsored by Persistent Systems. Luis Rocha, Director of the Complex Systems PhD track in the School of Information and Computing at Indiana University Bloomington, explains the new software-driven approach to medical research. Big data generated through social media such as Twitter and Instragram provides a far deeper and fuller examination of the impact of medicines and diseases, leading to greater actionable insights to improve the efficacy of prevention and treatment.
Congratulations to Luis Rocha, who has been awarded a Fulbright Scholarship devoted to developing Complex Systems methodologies for the Life Sciences. The 12-month sabbatical is to be pursued under the Fulbright program for educational exchanges between the United States and Portugal. It will focus on studying collective behavior and control in biochemical and social networks. The broader goal is to advance our ability to predict and control the dynamics of complex networks in three domain areas: biochemical, neurodyamic, and social systems. The scholarship will also be used to facilitate the design of a new doctoral program on complex networks and systems for the life sciences.
Update: On March 21st, 2016 the paper described below (PMC4720984) was highlighted by Russ Altman from Stanford University in his yearly review as one of 30 important papers of the year in translational bioinformatics.
Using complex networks analysis and social media mining, CNETS researchers from the CASCI team have found that Instagram, a growing social media platform among teens, can be used “to uncover drug-drug interactions (DDI) and adverse drug reactions (ADR).” The work shows that this popular social media service is “a very powerful source of data with great promise in the public-health domain”. The study, “Monitoring Potential Drug Interactions and Reactions via Network Analysis of Instagram User Timelines,” supported by an R01 grant from the National Institutes of Health as well as a gift from Persistent Inc., was recently published and presented at the Pacific Symposium on Biocomputing (PSB 2016), in Hawaii. (PubMed, arXiv). The results are based on almost 7.000 user timelines associated with depression drugs which combined have 5+ million posts.
Read our latest paper titled Canalization and Control in Automata Networks: Body Segmentation in Drosophila melanogaster in PLoS ONE. Authors Manuel Marques-Pita & Luis Rocha ask, How do cells and tissues ‘compute’? Schema redescription is presented as a methodology to characterize canalization in automata networks used to model biochemical regulation and signalling. Canalization becomes synonymous with redundancy present in the logic of automata. This results in straightforward measures to quantify canalization in an automaton (micro-level), which is in turn integrated into a highly scalable framework to characterize the collective dynamics of large-scale automata networks (macro-level). Several new results ensue from this methodology developed as part of the CASCI collective dynamics project: uncovering of dynamical modularity (modules in the dynamics rather than in the structure of networks), identification of minimal conditions and critical nodes to control the convergence to attractors, simulation of dynamical behaviour from incomplete information about initial conditions, and measures of macro-level canalization and robustness to perturbations. The methodology is applicable to any complex network that can be modelled using automata, but this work focuses on biochemical regulation and signalling, with a well-known model of the intra- and inter cellular genetic regulation of body segmentation in Drosophila melanogaster.
The pharmacokinetics ontology and corpus for text mining developed in collaboration with Li’s lab at IUPUI, part of CASCI Biomedical Literature Mining work, has been reported in BMC Bioinformatics where it has become a Highly Accessed paper:
Wu, Hengyi, S. Karnik, A. Subhadarshini, Z. Wang, S. Philips, X. Han, C. Chiang, L. Liu, M. Boustani, L.M. Rocha, S.K. Quinney, D.A. Flockhart and L. Li . “An Integrated Pharmacokinetics Ontology and Corpus for Text Mining”. BMC Bioinformatics. 14:35. DOI:10.1186/1471-2105-14-35.