Investigating information storage and processing in biological systems
We work on novel ways to understand and control complex pattern formation. We use techniques of molecular genetics, biophysics, and computational modeling to address large-scale control of growth and form. We work in whole frogs and flatworms, and sometimes zebrafish and human tissues in culture. Our projects span regeneration, embryogenesis, cancer, and learning plasticity – all examples of how cellular networks process information. In all of these efforts, our goal is not only to understand the molecular mechanisms necessary for morphogenesis, but also to uncover and exploit the cooperative signaling dynamics that enable complex bodies to build and remodel themselves toward a correct structure. Our major goal is to understand how individual cell behaviors are orchestrated towards appropriate large-scale outcomes despite unpredictable environmental perturbations.
Tag: computational biology
👓 A Conversation with @LPachter (BS ’94) | Caltech
Pachter, a computational biologist, returns to CalTech to study the role and function of RNA.
IPAM Workshop on Regulatory and Epigenetic Stochasticity in Development and Disease, March 1-3
Epigenetics refers to information transmitted during cell division other than the DNA sequence per se, and it is the language that distinguishes stem cells from somatic cells, one organ from another, and even identical twins from each other. In contrast to the DNA sequence, the epigenome is relatively susceptible to modification by the environment as well as stochastic perturbations over time, adding to phenotypic diversity in the population. Despite its strong ties to the environment, epigenetics has never been well reconciled to evolutionary thinking, and in fact there is now strong evidence against the transmission of so-called “epi-alleles,” i.e. epigenetic modifications that pass through the germline.
However, genetic variants that regulate stochastic fluctuation of gene expression and phenotypes in the offspring appear to be transmitted as an epigenetic or even Lamarckian trait. Furthermore, even the normal process of cellular differentiation from a single cell to a complex organism is not understood well from a mathematical point of view. There is increasingly strong evidence that stem cells are highly heterogeneous and in fact stochasticity is necessary for pluripotency. This process appears to be tightly regulated through the epigenome in development. Moreover, in these biological contexts, “stochasticity” is hardly synonymous with “noise”, which often refers to variation which obscures a “true signal” (e.g., measurement error) or which is structural, as in physics (e.g., quantum noise). In contrast, “stochastic regulation” refers to purposeful, programmed variation; the fluctuations are random but there is no true signal to mask.
This workshop will serve as a forum for scientists and engineers with an interest in computational biology to explore the role of stochasticity in regulation, development and evolution, and its epigenetic basis. Just as thinking about stochasticity was transformative in physics and in some areas of biology, it promises to fundamentally transform modern genetics and help to explain phase transitions such as differentiation and cancer.
This workshop will include a poster session; a request for poster titles will be sent to registered participants in advance of the workshop.
Adam Arkin (Lawrence Berkeley Laboratory)
Gábor Balázsi (SUNY Stony Brook)
Domitilla Del Vecchio (Massachusetts Institute of Technology)
Michael Elowitz (California Institute of Technology)
Andrew Feinberg (Johns Hopkins University)
Don Geman (Johns Hopkins University)
Anita Göndör (Karolinska Institutet)
John Goutsias (Johns Hopkins University)
Garrett Jenkinson (Johns Hopkins University)
Andre Levchenko (Yale University)
Olgica Milenkovic (University of Illinois)
Johan Paulsson (Harvard University)
Leor Weinberger (University of California, San Francisco (UCSF))
Ten Simple Rules for Taking Advantage of Git and GitHub
Bioinformatics is a broad discipline in which one common denominator is the need to produce and/or use software that can be applied to biological data in different contexts. To enable and ensure the replicability and traceability of scientific claims, it is essential that the scientific publication, the corresponding datasets, and the data analysis are made publicly available [1,2]. All software used for the analysis should be either carefully documented (e.g., for commercial software) or, better yet, openly shared and directly accessible to others [3,4]. The rise of openly available software and source code alongside concomitant collaborative development is facilitated by the existence of several code repository services such as SourceForge, Bitbucket, GitLab, and GitHub, among others. These resources are also essential for collaborative software projects because they enable the organization and sharing of programming tasks between different remote contributors. Here, we introduce the main features of GitHub, a popular web-based platform that offers a free and integrated environment for hosting the source code, documentation, and project-related web content for open-source projects. GitHub also offers paid plans for private repositories (see Box 1) for individuals and businesses as well as free plans including private repositories for research and educational use.
BIRS Workshop: Advances and Challenges in Protein-RNA: Recognition, Regulation and Prediction (15w5063)
BIRS 5 day worksop, arriving in Banff, Alberta Sunday, June 7 and departing Friday, June 12, 2015
In the years since the first assembly of the human genome, the complex and vital role of RNA and RNA binding proteins in regulation of the genome expression has expanded through the discovery of RNA-binding proteins and large classes of non-coding RNA that control many developmental decisions as part of protein- RNA complexes. Our molecular level understanding of RNA regulation has dramatically improved as many new structures of RNA–protein complexes have been determined and new sophisticated experimental technologies and dedicated computational modeling have emerged to investigate these interactions at the whole-genome level. Further deep insight on the molecular mechanisms that underline genome expression regulation is critical for understanding fundamental biology and disease progression towards the discovery of new approaches to interfere with disease progression.
The proposed workshop will bring together experts in RNA biology with structural biologists that focus on RNA-protein complexes, as well as computational biologists who seek to model and develop predictive tools based on the confluence of these experimental advances. The workshop intends to foster new collaborations between experimental and computational biologists and catalyze the development of new and improved technologies (such as single cell binding methods) that merge experimental analysis with novel mathematical and computational techniques to better understand the rules of protein-RNA recognition and RNA-based biological regulation.
The organizers of the workshop are both leaders in the field of protein-RNA recognition and interactions: Yael Mandel-Gutfreund has been working in the field of protein-Nucleic Acids interactions since 1994. Her main research interest is protein-RNA recognition and regulation. She has developed several tools and web servers for predicting RNA binding proteins and RNA binding motifs. Yael is the head to the computational molecular laboratory at the Technion and the president of the Israeli society of Bioinformatics and Computational Biology. Gabriele Varani has been working in the field of RNA structure and protein-RNA interactions since 1987. His main research interest is the structural basis for protein-RNA recognition and the prediction and design of RNA-binding proteins. He determined some of the first few structures of protein-RNA complexes and developed computational tools to analyze and predict the specificity of RNA -binding proteins. His group applies these tools to design RNA-binding proteins with new specificity to control gene expression. Our invitation to participate in the workshop has been met with great enthusiasm by the researchers. More than 20 principle investigators have already confirmed their interest in attending. Six of the confirmed participants are female scientists including the organizer Yael Mandel-Gutfreund as well as Traci Hall, Lynne Maquat, Elena Conti, Susan Jones, Drena Dobbs. We also have invited and confirmed the participation of young and promising researchers including Markus Landthaler, Gene Yeo, Jernej Ule, Uwe Ohler and others. Our confirmed participants come from many different countries: US, Canada, UK, Scotland, Germany, Spain, Switzerland, Poland and Israel. Two confirmed participants as well as the organizer have attended the BIRS workshops in the past.
A key objective of the workshop is to bring together researchers with experimental, mathematical and computational background to share results and discuss the main advances and challenges in the prediction, analysis and control of RNA-protein recognition and RNA-based regulation of gene expression. Towards this aim, we plan to adopt the format of previous BIRS meetings in which invited participants (including selected students) will present relatively short presentations of 20 minutes plus 10 minutes of active discussions. This format will leave aside ample time for informal discussions to foster exchanges between participants. To stress the collaborative, multidisciplinary nature of the workshop, we plan to dedicate each of the workshop sessions to a specific topic that will comprise presentations of structural, experimental and computational approaches, rather than create session focused on a particular approach. Each session we will include at least one lecture from a young scientist/postdoctoral fellow/student to be chosen among attendees by the organizers.
Suggested preliminary schedule:
- Day 1: Modeling and high throughput approaches to genome-wide analysis of protein-RNA interactions
- Day 2: Predicting and designing new RNA binding proteins
- Day 3: Generating and modeling RNA-based regulatory networks
- Day 4: Principles of RNA regulation by RNA binding proteins
- Day 5: Conclusion round table discussion on the present and future challenges of the field