Richard Watson  | Institute for Life Sciences/ Department of Computer Science (Agents, Interaction and Complexity group), University of Southampton

Title: Learning, memory and adaptation before evolution

Abstract: Forthcoming

Stephen Wolfram  | Founder & CEO of Wolfram Research

Title: Computational irreducibility and minimal models of biology

Abstract: Forthcoming

Title: Programmable Protein Therapeutics via Generative Language Models

Abstract:

CRISPR has revolutionized biotechnology by enabling the simple design of guide RNAs to target and edit almost any DNA sequence. By developing new generative protein design algorithms, my hybrid lab focuses on extending this CRISPR-like programmability to proteins and other key molecules. In this talk, we will first delve into our algorithms that design binders to undruggable proteins, such as those driving pediatric cancers (alveolar rhabdomyosarcoma and Ewing’s sarcoma) and neurodegenerative diseases (Huntington’s and Alexander Disease). Our generative language models, including SaLT&PepPr, PepPrCLIP, and PepMLM, design short binding peptides from target sequence alone, with no dependence on stable 3D structures, and by fusing these "guide" peptides to E3 ubiquitin ligases, deubiquitinases, and other modifying enzymes, we have created a CRISPR-analogous system to edit these proteins. To be even more specific, we train isoform-specific targeting models such as PTM-Mamba for PTM-specific binding, FusOn-pLM for fusion oncoprotein-specific degradation, and moPPIt for motif-specific targeting of protein-protein interactions. Inspired by the power of language models, we further show how we can extend this programmability to DNA with our PAM-free CRISPR enzymes and our recent DPAC model, as well as heavy metals through our MetaLATTE algorithm and chemical pollutants, such as PFAS. Finally, we will explore our long-term goal of generating new cell states with model-designed proteins, highlighting our recent work on transcription factor-directed stem cell differentiation to ovarian cell types, such as granulosa cells and oogonia. By combining generative design with experimental engineering, our hybrid lab aims to translate these advances into practical applications for treating intractable diseases and addressing environmental challenges.

Stacey Finley | University of Southern California Viterbi School of Engineering 

Title: Studying the tumor microenvironment as an ecosystem

Abstract: Forthcoming

Adam Palmer  | University of North Carolina

Title: How combination therapy cures some cancers

Abstract: Forthcoming

Mohit Kumar Jolly  | Biological Sciences Building Indian Institute of Science, Bengaluru, India

Title: Low dimensionality of phenotypic space as an emergent property of biological regulatory networks

Abstract: Forthcoming

Zev Gartner | University of California at San Francisco

Title:  Order from disorder: self-organization in development and disease

Abstract: Forthcoming

Professor, Department of Molecular and Cellular Biology, University of California, Berkeley
Talk Title: "The past has left its traces on the world.”: deeply conserved synteny and the evolution of animals
Host: Marcos Simoes-Costa
Food to be Provided

On Zoom and in WAB 563

Pizza Talks: Rikki Garner, Megason Lab

Talk Title: Cell migration: Noise and robustness in spatial patterning across scales

Matthew Fisher | Kavli Institute for Theoretical Physics UC Santa Barbara

Title: Quantum processing in the brain?

Abstract: The endeavor to construct a laboratory quantum computer has evolved into a multi-billion-dollar undertaking. However, an intriguing question arises: could we ourselves be quantum computers? While maintaining quantum coherence on macroscopic time scales is exceedingly unlikely in the warm wet brain, there is one exception: nuclear spins. Our strategy is one of reverse engineering, seeking to pinpoint the biochemical substrate and mechanisms that might underpin the hypothetical quantum processing involving nuclear spins. Seemingly, a specific neural qubit and a unique collection of ions, molecules and organelles can be identified. I will present an overview of our (largely experimental) ongoing efforts to delve into this captivating realm of exploration.

Assistant Professor, Laboratory of the Physics of Biological Systems, Institute of Physics, EPFL 
Talk Title: “Why and how the DNA damage checkpoint gambles with cells' future + Preview: evolving switchable proteins.”
Host: Galit Lahav
Food to be Provided

Michael Baym  | Harvard Medical School

Title: Plasmid ecology

Abstract: Forthcoming

Guillaume Montagnac |Gustave Roussy Cancer Campus |Paris, FRANCE

Title: Associative memory in human cancer cells

Abstract : In psychology and neuroscience, associative memory refers to the capacity to learn and remember a link between two unrelated items. Although associative memory is widely believed to be restricted to animals possessing a complex nervous system, several reports have suggested that single-cell organisms can be conditioned to develop an associative memory-like behavior. Here, we report that human cancer cell lines can be conditioned to associate an extracellular matrix component and Gefitinib, a drug that reduces cell migration velocity. Collagen-I was periodically paired with Gefitinib and we observed that conditioned cells progressive decreased migration velocity on collagen-I but not on other extracellular matrix components. We identified the adenosine receptor ADORA2A as a key actor regulating the acquisition of associative memory. We also observed that the magnitude of the conditioned response oscillated over time with the same periodicity as paired stimuli presentations during conditioning. We found that mitochondria morphology oscillated with the same periodicity, suggesting that memory and energy metabolisms are linked. We propose that human cancer cells can be conditioned to integrate a link between two stimuli from their environment in a process that may allow to anticipate future stress exposition.

On Zoom and in WAB 563

Pizza Talks: Michael Cory, Silver Lab

Talk Title: Rare No Longer: Harnessing the Power of Biology for the Sustainable Purification of Rare Earth Metals

Gautam Reddy | Department of Physics | Princeton University

Talk Title: Dynamic landscapes during cellular growth and diversification

Abstract: The complexity of gene regulatory networks in multicellular organisms makes interpretable low-dimensional models highly desirable. An attractive geometric picture, attributed to Waddington, visualizes the differentiation of a cell into diverse functional types as gradient flow on a dynamic potential landscape, but it is unclear under what biological constraints this metaphor is mathematically precise. In this talk, I will show that gene regulatory strategies that guide the growth and development of a single cell to a target distribution of cell types are described by time-dependent potential landscapes, under certain specific growth-control tradeoffs. The theory highlights a conceptual link between nonequilibrium thermodynamics and cellular decision-making during development.

Theory Lunch Zoom Details:

https://harvard.zoom.us/j/94761157754?pwd=kvdkMldvwFaZAeMOvXzMPeP5Pyne30.1 | PW: 10042024

Talk title: Predicting and discovering protein dynamics

Abstract: The functions of biomolecules are often based in their ability to convert between multiple conformations. Recent advances in deep learning for predicting and designing single structures of proteins mean that the next frontier lies in how well we can characterize, model, and predict protein dynamics. In the first part of my talk, I will describe a simple adaptation of AlphaFold to predict multiple conformations, and my work combining the resulting “AF-Cluster” method and NMR dynamics experiments to learn more about how timing in the circadian rhythm protein KaiB is encoded in its sequence. However, a major bottleneck for the field of predicting dynamics has been a lack of standardized datasets of experimental kinetics measurements, and especially those on a micro-millisecond timescale where many biologically-relevant processes occur. In the second part of my talk, I will describe the development of large-scale benchmarks of dynamics from across multiple types of NMR experiments, and initial insights from training deep learning models to predict these hallmarks of dynamics.

On Zoom and in WAB 563

Pizza Talks: Haig Alexander Eskandarian, Paulsson Lab

Talk Title: Uncovering a "New Microbiology" using Long -Term Time-Lapse Atomic Force Microscopy

Title: Engineering TCR-controlled Fuzzy Logic into CAR T Cells Enhances Therapeutic Specificity

WAB 563

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