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Cross-evaluation of E. coli’s operon structures via a whole-cell model suggests alternative cellular benefits for low- versus high-expressing operons Cell Syst. (IF 9.3) Pub Date : 2024-02-27 Gwanggyu Sun, Mialy M. DeFelice, Taryn E. Gillies, Travis A. Ahn-Horst, Cecelia J. Andrews, Markus Krummenacker, Peter D. Karp, Jerry H. Morrison, Markus W. Covert
Many bacteria use operons to coregulate genes, but it remains unclear how operons benefit bacteria. We integrated ’s 788 polycistronic operons and 1,231 transcription units into an existing whole-cell model and found inconsistencies between the proposed operon structures and the RNA-seq read counts that the model was parameterized from. We resolved these inconsistencies through iterative, model-guided
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Clonal differences underlie variable responses to sequential and prolonged treatment Cell Syst. (IF 9.3) Pub Date : 2024-02-23 Dylan L. Schaff, Aria J. Fasse, Phoebe E. White, Robert J. Vander Velde, Sydney M. Shaffer
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High immigration rates critical for establishing emigration-driven diversity in microbial communities Cell Syst. (IF 9.3) Pub Date : 2024-02-23 Xiaoli Chen, Miaoxiao Wang, Laipeng Luo, Liyun An, Xiaonan Liu, Yuan Fang, Ting Huang, Yong Nie, Xiao-Lei Wu
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A top variant identification pipeline for protein engineering Cell Syst. (IF 9.3) Pub Date : 2024-02-21 Hui Chen, Zhike Lu, Lijia Ma
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Mapping combinatorial expression perturbations to growth in Escherichia coli Cell Syst. (IF 9.3) Pub Date : 2024-02-21 J. Scott P. McCain
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Single-cell colocalization analysis using a deep generative model Cell Syst. (IF 9.3) Pub Date : 2024-02-21 Yasuhiro Kojima, Shinji Mii, Shuto Hayashi, Haruka Hirose, Masato Ishikawa, Masashi Akiyama, Atsushi Enomoto, Teppei Shimamura
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Widespread alteration of protein autoinhibition in human cancers Cell Syst. (IF 9.3) Pub Date : 2024-02-15 Jorge A. Holguin-Cruz, Jennifer M. Bui, Ashwani Jha, Dokyun Na, Jörg Gsponer
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A continuous epistasis model for predicting growth rate given combinatorial variation in gene expression and environment Cell Syst. (IF 9.3) Pub Date : 2024-02-09 Ryan M. Otto, Agata Turska-Nowak, Philip M. Brown, Kimberly A. Reynolds
Quantifying and predicting growth rate phenotype given variation in gene expression and environment is complicated by epistatic interactions and the vast combinatorial space of possible perturbations. We developed an approach for mapping expression-growth rate landscapes that integrates sparsely sampled experimental measurements with an interpretable machine learning model. We used mismatch CRISPRi
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Clonally heritable gene expression imparts a layer of diversity within cell types Cell Syst. (IF 9.3) Pub Date : 2024-02-09 Jeff E. Mold, Martin H. Weissman, Michael Ratz, Michael Hagemann-Jensen, Joanna Hård, Carl-Johan Eriksson, Hosein Toosi, Joseph Berghenstråhle, Christoph Ziegenhain, Leonie von Berlin, Marcel Martin, Kim Blom, Jens Lagergren, Joakim Lundeberg, Rickard Sandberg, Jakob Michaëlsson, Jonas Frisén
Cell types can be classified according to shared patterns of transcription. Non-genetic variability among individual cells of the same type has been ascribed to stochastic transcriptional bursting and transient cell states. Using high-coverage single-cell RNA profiling, we asked whether long-term, heritable differences in gene expression can impart diversity within cells of the same type. Studying
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Accurate top protein variant discovery via low-N pick-and-validate machine learning Cell Syst. (IF 9.3) Pub Date : 2024-02-09 Hoi Yee Chu, John H.C. Fong, Dawn G.L. Thean, Peng Zhou, Frederic K.C. Fung, Yuanhua Huang, Alan S.L. Wong
A strategy to obtain the greatest number of best-performing variants with least amount of experimental effort over the vast combinatorial mutational landscape would have enormous utility in boosting resource producibility for protein engineering. Toward this goal, we present a simple and effective machine learning-based strategy that outperforms other state-of-the-art methods. Our strategy integrates
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Retrospective identification of cell-intrinsic factors that mark pluripotency potential in rare somatic cells Cell Syst. (IF 9.3) Pub Date : 2024-02-08 Naveen Jain, Yogesh Goyal, Margaret C. Dunagin, Christopher J. Cote, Ian A. Mellis, Benjamin Emert, Connie L. Jiang, Ian P. Dardani, Sam Reffsin, Miles Arnett, Wenli Yang, Arjun Raj
Pluripotency can be induced in somatic cells by the expression of OCT4, KLF4, SOX2, and MYC. Usually only a rare subset of cells reprogram, and the molecular characteristics of this subset remain unknown. We apply retrospective clone tracing to identify and characterize the rare human fibroblasts primed for reprogramming. These fibroblasts showed markers of increased cell cycle speed and decreased
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Simple visualization of submicroscopic protein clusters with a phase-separation-based fluorescent reporter Cell Syst. (IF 9.3) Pub Date : 2024-02-08 Thomas R. Mumford, Diarmid Rae, Emily Brackhahn, Abbas Idris, David Gonzalez-Martinez, Ayush Aditya Pal, Michael C. Chung, Juan Guan, Elizabeth Rhoades, Lukasz J. Bugaj
Protein clustering plays numerous roles in cell physiology and disease. However, protein oligomers can be difficult to detect because they are often too small to appear as puncta in conventional fluorescence microscopy. Here, we describe a fluorescent reporter strategy that detects protein clusters with high sensitivity called CluMPS (clusters magnified by phase separation). A CluMPS reporter detects
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Modes and motifs in multicellular communication Cell Syst. (IF 9.3) Pub Date : 2024-01-17 Anna C. Kögler, Patrick Müller
Signaling pathways feature multiple interacting ligand and receptor variants, which are thought to act in a combinatorial manner to elicit different cellular responses. Transcriptome analyses now suggest that many signaling pathways use their components in combinations that are surprisingly often shared between otherwise dissimilar cell states.
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Controlled exchange of protein and nucleic acid signals from and between synthetic minimal cells Cell Syst. (IF 9.3) Pub Date : 2024-01-17 Joseph M. Heili, Kaitlin Stokes, Nathaniel J. Gaut, Christopher Deich, Judee Sharon, Tanner Hoog, Jose Gomez-Garcia, Brock Cash, Matthew R. Pawlak, Aaron E. Engelhart, Katarzyna P. Adamala
Synthetic minimal cells are a class of bioreactors that have some, but not all, functions of live cells. Here, we report a critical step toward the development of a bottom-up minimal cell: cellular export of functional protein and RNA products. We used cell-penetrating peptide tags to translocate payloads across a synthetic cell vesicle membrane. We demonstrated efficient transport of active enzymes
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The trade-off between individual metabolic specialization and versatility determines the metabolic efficiency of microbial communities Cell Syst. (IF 9.3) Pub Date : 2024-01-17 Miaoxiao Wang, Xiaoli Chen, Yuan Fang, Xin Zheng, Ting Huang, Yong Nie, Xiao-Lei Wu
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Predicting gene-level sensitivity to JAK-STAT signaling perturbation using a mechanistic-to-machine learning framework Cell Syst. (IF 9.3) Pub Date : 2024-01-09 Neha Cheemalavagu, Karsen E. Shoger, Yuqi M. Cao, Brandon A. Michalides, Samuel A. Botta, James R. Faeder, Rachel A. Gottschalk
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Single-cell sequencing analysis within biologically relevant dimensions Cell Syst. (IF 9.3) Pub Date : 2024-01-09 Robert Kousnetsov, Jessica Bourque, Alexey Surnov, Ian Fallahee, Daniel Hawiger
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Meta learning addresses noisy and under-labeled data in machine learning-guided antibody engineering Cell Syst. (IF 9.3) Pub Date : 2024-01-08 Mason Minot, Sai T. Reddy
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Apparent simplicity and emergent robustness in the control of the Escherichia coli cell cycle Cell Syst. (IF 9.3) Pub Date : 2023-12-28 Sander K. Govers, Manuel Campos, Bhavyaa Tyagi, Géraldine Laloux, Christine Jacobs-Wagner
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Startle: A star homoplasy approach for CRISPR-Cas9 lineage tracing Cell Syst. (IF 9.3) Pub Date : 2023-12-20 Palash Sashittal, Henri Schmidt, Michelle Chan, Benjamin J. Raphael
CRISPR-Cas9-based genome editing combined with single-cell sequencing enables the tracing of the history of cell divisions, or cellular lineage, in tissues and whole organisms. Although standard phylogenetic approaches may be applied to reconstruct cellular lineage trees from this data, the unique features of the CRISPR-Cas9 editing process motivate the development of specialized models that describe
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Robustness and complexity Cell Syst. (IF 9.3) Pub Date : 2023-12-20 Steven A. Frank
When a system robustly corrects component-level errors, the direct pressure on component performance declines. Components become less reliable, maintain more genetic variability, or drift neutrally, creating new forms of complexity. Examples include the hourglass pattern of biological development and the hourglass architecture for robustly complex systems in engineering.
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Modeling elucidates context dependence in adipose regulation Cell Syst. (IF 9.3) Pub Date : 2023-12-20 Cameron D. Vasquez, John G. Albeck
Single-cell data and computational simulations reveal the dynamics of the transcription factors HIF1α and PPARγ during adipocyte differentiation and maturation. Modeling feedback within this network predicts a HIF1α-mediated choice between lipid accumulation and incomplete differentiation. In vitro experiments support this model, with implications for adipose dynamics in metabolic disorders involving
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Advances in ligand-specific biosensing for structurally similar molecules Cell Syst. (IF 9.3) Pub Date : 2023-12-20 Chenggang Xi, Jinjin Diao, Tae Seok Moon
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HOGVAX: Exploiting epitope overlaps to maximize population coverage in vaccine design with application to SARS-CoV-2 Cell Syst. (IF 9.3) Pub Date : 2023-12-20 Sara C. Schulte, Alexander T. Dilthey, Gunnar W. Klau
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Inference of differentiation trajectories by transfer learning across biological processes Cell Syst. (IF 9.3) Pub Date : 2023-12-20 Gaurav Jumde, Bastiaan Spanjaard, Jan Philipp Junker
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Deep learning and CRISPR-Cas13d ortholog discovery for optimized RNA targeting Cell Syst. (IF 9.3) Pub Date : 2023-12-12 Jingyi Wei, Peter Lotfy, Kian Faizi, Sara Baungaard, Emily Gibson, Eleanor Wang, Hannah Slabodkin, Emily Kinnaman, Sita Chandrasekaran, Hugo Kitano, Matthew G. Durrant, Connor V. Duffy, April Pawluk, Patrick D. Hsu, Silvana Konermann
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Control points for design of taxonomic composition in synthetic human gut communities Cell Syst. (IF 9.3) Pub Date : 2023-12-12 Bryce M. Connors, Jaron Thompson, Sarah Ertmer, Ryan L. Clark, Brian F. Pfleger, Ophelia S. Venturelli
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Machine learning analysis of the T cell receptor repertoire identifies sequence features of self-reactivity Cell Syst. (IF 9.3) Pub Date : 2023-12-06 Johannes Textor, Franka Buytenhuijs, Dakota Rogers, Ève Mallet Gauthier, Shabaz Sultan, Inge M.N. Wortel, Kathrin Kalies, Anke Fähnrich, René Pagel, Heather J. Melichar, Jürgen Westermann, Judith N. Mandl
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Discovery of regulatory motifs in 5′ untranslated regions using interpretable multi-task learning models Cell Syst. (IF 9.3) Pub Date : 2023-11-27 Weizhong Zheng, John H.C. Fong, Yuk Kei Wan, Athena H.Y. Chu, Yuanhua Huang, Alan S.L. Wong, Joshua W.K. Ho
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Context-dependent regulation of lipid accumulation in adipocytes by a HIF1α-PPARγ feedback network Cell Syst. (IF 9.3) Pub Date : 2023-11-22 Takamasa Kudo, Michael L. Zhao, Stevan Jeknić, Kyle M. Kovary, Edward L. LaGory, Markus W. Covert, Mary N. Teruel
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Becoming fluent in proteins Cell Syst. (IF 9.3) Pub Date : 2023-11-15 Jinwoo Leem, Jacob D. Galson
Large language models have emerged as a new compass for navigating the complex landscapes of protein engineering. This issue of Cell Systems features ProGen2 and IgLM—two protein language models (PLMs) that use subtly different approaches to design proteins.
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A new age in protein design empowered by deep learning Cell Syst. (IF 9.3) Pub Date : 2023-11-15 Hamed Khakzad, Ilia Igashov, Arne Schneuing, Casper Goverde, Michael Bronstein, Bruno Correia
The rapid progress in the field of deep learning has had a significant impact on protein design. Deep learning methods have recently produced a breakthrough in protein structure prediction, leading to the availability of high-quality models for millions of proteins. Along with novel architectures for generative modeling and sequence analysis, they have revolutionized the protein design field in the
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Optimal control of gene regulatory networks for morphogen-driven tissue patterning Cell Syst. (IF 9.3) Pub Date : 2023-11-15 Alberto Pezzotta, James Briscoe
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Millennia-long epigenetic fluctuations generate intragenic DNA methylation variance in Arabidopsis populations Cell Syst. (IF 9.3) Pub Date : 2023-11-08 Amy Briffa, Elizabeth Hollwey, Zaigham Shahzad, Jonathan D. Moore, David B. Lyons, Martin Howard, Daniel Zilberman
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Genome-wide identification of overexpression and downregulation gene targets based on the sum of covariances of the outgoing reaction fluxes Cell Syst. (IF 9.3) Pub Date : 2023-11-06 Won Jun Kim, Youngjoon Lee, Hyun Uk Kim, Jae Yong Ryu, Jung Eun Yang, Sang Yup Lee
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A framework for ultra-low-input spatial tissue proteomics Cell Syst. (IF 9.3) Pub Date : 2023-10-30 Anuar Makhmut, Di Qin, Sonja Fritzsche, Jose Nimo, Janett König, Fabian Coscia
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IgLM: Infilling language modeling for antibody sequence design Cell Syst. (IF 9.3) Pub Date : 2023-10-30 Richard W. Shuai, Jeffrey A. Ruffolo, Jeffrey J. Gray
Discovery and optimization of monoclonal antibodies for therapeutic applications relies on large sequence libraries but is hindered by developability issues such as low solubility, high aggregation, and high immunogenicity. Generative language models, trained on millions of protein sequences, are a powerful tool for the on-demand generation of realistic, diverse sequences. We present the Immunoglobulin
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ProGen2: Exploring the boundaries of protein language models Cell Syst. (IF 9.3) Pub Date : 2023-10-30 Erik Nijkamp, Jeffrey A. Ruffolo, Eli N. Weinstein, Nikhil Naik, Ali Madani
Attention-based models trained on protein sequences have demonstrated incredible success at classification and generation tasks relevant for artificial-intelligence-driven protein design. However, we lack a sufficient understanding of how very large-scale models and data play a role in effective protein model development. We introduce a suite of protein language models, named ProGen2, that are scaled
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Genome-wide measurement of RNA dissociation from chromatin classifies transcripts by their dynamics and reveals rapid dissociation of enhancer lncRNAs Cell Syst. (IF 9.3) Pub Date : 2023-10-18 Evgenia Ntini, Stefan Budach, Ulf A. Vang Ørom, Annalisa Marsico
Long non-coding RNAs (lncRNAs) are involved in gene expression regulation in cis. Although enriched in the cell chromatin fraction, to what degree this defines their regulatory potential remains unclear. Furthermore, the factors underlying lncRNA chromatin tethering, as well as the molecular basis of efficient lncRNA chromatin dissociation and its impact on enhancer activity and target gene expression
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Observations and implication of thermal tolerance in the Arabidopsis proteome Cell Syst. (IF 9.3) Pub Date : 2023-10-18 Alisdair R. Fernie, Youjun Zhang
Knowledge of the thermal stability of plant proteomes within their native environments would aid in the design of climate-resilient crop plants. Identification of thermo-sensitive and -resilient proteins not only provides foundational understanding of systematic heat-induced damage but also offers insight into protein interactions and protein evolution.
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Genomic footprinting uncovers global transcription factor responses to amino acids in Escherichia coli Cell Syst. (IF 9.3) Pub Date : 2023-10-10 Julian Trouillon, Peter F. Doubleday, Uwe Sauer
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Volumetric compression by heterogeneous scaffold embedding promotes cerebral organoid maturation and does not impede growth Cell Syst. (IF 9.3) Pub Date : 2023-10-10 Xiaowei Tang, Zitian Wang, Davit Khutsishvili, Yifan Cheng, Jiaqi Wang, Jiyuan Tang, Shaohua Ma
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Promotion of plasmid maintenance by heterogeneous partitioning of microbial communities Cell Syst. (IF 9.3) Pub Date : 2023-10-10 Andrea Weiss, Teng Wang, Lingchong You
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Studying stochastic systems biology of the cell with single-cell genomics data Cell Syst. (IF 9.3) Pub Date : 2023-09-25 Gennady Gorin, John J. Vastola, Lior Pachter
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DNA-GPS: A theoretical framework for optics-free spatial genomics and synthesis of current methods Cell Syst. (IF 9.3) Pub Date : 2023-09-25 Laura Greenstreet, Anton Afanassiev, Yusuke Kijima, Matthieu Heitz, Soh Ishiguro, Samuel King, Nozomu Yachie, Geoffrey Schiebinger
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What cannot be seen correctly in 2D visualizations of single-cell ‘omics data? Cell Syst. (IF 9.3) Pub Date : 2023-09-20 Shu Wang, Eduardo D. Sontag, Douglas A. Lauffenburger
A common strategy for exploring single-cell ‘omics data is visualizing 2D nonlinear projections that aim to preserve high-dimensional data properties such as neighborhoods. Alternatively, mathematical theory and other computational tools can directly describe data geometry, while also showing that neighborhoods and other properties cannot be well-preserved in any 2D projection.
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A microwell platform for high-throughput longitudinal phenotyping and selective retrieval of organoids Cell Syst. (IF 9.3) Pub Date : 2023-09-20 Alexandra Sockell, Wing Wong, Scott Longwell, Thy Vu, Kasper Karlsson, Daniel Mokhtari, Julia Schaepe, Yuan-Hung Lo, Vincent Cornelius, Calvin Kuo, David Van Valen, Christina Curtis, Polly M. Fordyce
Organoids are powerful experimental models for studying the ontogeny and progression of various diseases including cancer. Organoids are conventionally cultured in bulk using an extracellular matrix mimic. However, bulk-cultured organoids physically overlap, making it impossible to track the growth of individual organoids over time in high throughput. Moreover, local spatial variations in bulk matrix
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Systematic thermal analysis of the Arabidopsis proteome: Thermal tolerance, organization, and evolution Cell Syst. (IF 9.3) Pub Date : 2023-09-20 Hai-Ning Lyu, Chunjin Fu, Xin Chai, Zipeng Gong, Junzhe Zhang, Jiaqi Wang, Jigang Wang, Lingyun Dai, Chengchao Xu
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Synthetic symmetry breaking and programmable multicellular structure formation Cell Syst. (IF 9.3) Pub Date : 2023-09-08 Noreen Wauford, Akshay Patel, Jesse Tordoff, Casper Enghuus, Andrew Jin, Jack Toppen, Melissa L. Kemp, Ron Weiss
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A bipartite function of ESRRB can integrate signaling over time to balance self-renewal and differentiation Cell Syst. (IF 9.3) Pub Date : 2023-08-25 Teresa E. Knudsen, William B. Hamilton, Martin Proks, Maria Lykkegaard, Madeleine Linneberg-Agerholm, Alexander V. Nielsen, Marta Perera, Luna Lynge Malzard, Ala Trusina, Joshua M. Brickman
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A proteogenomics data-driven knowledge base of human cancer Cell Syst. (IF 9.3) Pub Date : 2023-08-23 Yuxing Liao, Sara R. Savage, Yongchao Dou, Zhiao Shi, Xinpei Yi, Wen Jiang, Jonathan T. Lei, Bing Zhang
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How can the protein design community best support biologists who want to harness AI tools for protein structure prediction and design? Cell Syst. (IF 9.3) Pub Date : 2023-08-16 Birte Höcker, Peilong Lu, Anum Glasgow, Debora S. Marks, Pranam Chatterjee, Joanna S.G. Slusky, Ora Schueler-Furman, Possu Huang
Abstract not available
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Engineering allosteric transcription factors guided by the LacI topology Cell Syst. (IF 9.3) Pub Date : 2023-08-16 Ashley N. Hersey, Valerie E. Kay, Sumin Lee, Matthew J. Realff, Corey J. Wilson
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Simplifying complex antibody engineering using machine learning Cell Syst. (IF 9.3) Pub Date : 2023-08-16 Emily K. Makowski, Hsin-Ting Chen, Peter M. Tessier
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Protein engineering of pores for separation, sensing, and sequencing Cell Syst. (IF 9.3) Pub Date : 2023-08-16 Laxmicharan Samineni, Bibek Acharya, Harekrushna Behera, Hyeonji Oh, Manish Kumar, Ratul Chowdhury
Proteins are critical to cellular function and survival. They are complex molecules with precise structures and chemistries, which allow them to serve diverse functions for maintaining overall cell homeostasis. Since the discovery of the first enzyme in 1833, a gamut of advanced experimental and computational tools has been developed and deployed for understanding protein structure and function. Recent
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Learning protein fitness landscapes with deep mutational scanning data from multiple sources Cell Syst. (IF 9.3) Pub Date : 2023-08-16 Lin Chen, Zehong Zhang, Zhenghao Li, Rui Li, Ruifeng Huo, Lifan Chen, Dingyan Wang, Xiaomin Luo, Kaixian Chen, Cangsong Liao, Mingyue Zheng
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Uncovering the spatial landscape of molecular interactions within the tumor microenvironment through latent spaces Cell Syst. (IF 9.3) Pub Date : 2023-08-16 Atul Deshpande, Melanie Loth, Dimitrios N. Sidiropoulos, Shuming Zhang, Long Yuan, Alexander T.F. Bell, Qingfeng Zhu, Won Jin Ho, Cesar Santa-Maria, Daniele M. Gilkes, Stephen R. Williams, Cedric R. Uytingco, Jennifer Chew, Andrej Hartnett, Zachary W. Bent, Alexander V. Favorov, Aleksander S. Popel, Mark Yarchoan, Ashley Kiemen, Pei-Hsun Wu, Elana J. Fertig
Abstract not available
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High-throughput functional characterization of combinations of transcriptional activators and repressors Cell Syst. (IF 9.3) Pub Date : 2023-08-04 Adi X. Mukund, Josh Tycko, Sage J. Allen, Stephanie A. Robinson, Cecelia Andrews, Joydeb Sinha, Connor H. Ludwig, Kaitlyn Spees, Michael C. Bassik, Lacramioara Bintu
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The architecture of binding cooperativity between densely bound transcription factors Cell Syst. (IF 9.3) Pub Date : 2023-07-31 Offir Lupo, Divya Krishna Kumar, Rotem Livne, Michal Chappleboim, Idan Levy, Naama Barkai
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PocketAnchor: Learning structure-based pocket representations for protein-ligand interaction prediction Cell Syst. (IF 9.3) Pub Date : 2023-07-28 Shuya Li, Tingzhong Tian, Ziting Zhang, Ziheng Zou, Dan Zhao, Jianyang Zeng