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Designing biological sequences that satisfy multiple, often conflicting, functional and biophysical criteria remains a central challenge in biomolecule engineering.
Multiobjective optimization using evolutionary algorithms—a comparative case study
Eckart Zitzler and Lothar Thiele · 1998
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Spea2: Improving the strength pareto evolutionary algorithm
Eckart Zitzler, Marco Laumanns, and Lothar Thiele · 2001
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Mopso: A proposal for multiple objective particle swarm optimization
CA Coello Coello and Maximino Salazar Lechuga · 2002
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Challenges of continuous global optimization in molecular structure prediction
Gleb Beliakov and Kieran F Lim · 2007
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Sms-emoa: Multiobjective selection based on dominated hypervolume
Nicola Beume, Boris Naujoks, and Michael Emmerich · 2007
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Autodock vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading
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Multi-objective optimisation using evolutionary algorithms: an introduction
Kalyanmoy Deb · 2011
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Scikit-learn: Machine learning in Python
F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, and E. Duchesnay · 2011
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An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, part i: solving problems with box constraints
Kalyanmoy Deb and Himanshu Jain · 2013
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Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, dna-binding proteins and nucleosome position
Jason D Buenrostro, Paul G Giresi, Lisa C Zaba, Howard Y Chang, and William J Greenleaf · 2013
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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Crispr guide rna design for research applications
Stephanie E Mohr, Yanhui Hu, Benjamin Ewen-Campen, Benjamin E Housden, Raghuvir Viswanatha, and Norbert Perrimon · 2016
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Combo: An efficient bayesian optimization library for materials science
Tsuyoshi Ueno, Trevor David Rhone, Zhufeng Hou, Teruyasu Mizoguchi, and Koji Tsuda · 2016
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Peplife: a repository of the half-life of peptides
Deepika Mathur, Satya Prakash, Priya Anand, Harpreet Kaur, Piyush Agrawal, Ayesha Mehta, Rajesh Kumar, Sandeep Singh, and Gajendra PS Raghava · 2016
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Multi-objective de novo drug design with conditional graph generative model
Yibo Li, Liangren Zhang, and Zhenming Liu · 2018
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All-small-molecule organic solar cells with over 14% efficiency by optimizing hierarchical morphologies
Ruimin Zhou, Zhaoyan Jiang, Chen Yang, Jianwei Yu, Jirui Feng, Muhammad Abdullah Adil, Dan Deng, Wenjun Zou, Jianqi Zhang, Kun Lu, et al · 2019
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Optuna: A next-generation hyperparameter optimization framework
Takuya Akiba, Shotaro Sano, Toshihiko Yanase, Takeru Ohta, and Masanori Koyama · 2019
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Application of combinatorial optimization strategies in synthetic biology
Gita Naseri and Mattheos AG Koffas · 2020
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Novel strategies to optimize the amplification of single-stranded dna
Atef Nehdi, Nosaibah Samman, Vanessa Aguilar-Sánchez, Azer Farah, Emre Yurdusev, Mohamed Boudjelal, and Jonathan Perreault · 2020
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Therapeutic strategies to reduce the toxicity of misfolded protein oligomers
Ryan P Kreiser, Aidan K Wright, Natalie R Block, Jared E Hollows, Lam T Nguyen, Kathleen LeForte, Benedetta Mannini, Michele Vendruscolo, and Ryan Limbocker · 2020
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Bayesian optimization with evolutionary and structure-based regularization for directed protein evolution
Trevor S Frisby and Christopher James Langmead · 2021
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Combining multi-objective evolutionary algorithms with deep generative models towards focused molecular design
Tiago Sousa, João Correia, Vitor Pereira, and Miguel Rocha · 2021
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Misfolded protein oligomers: Mechanisms of formation, cytotoxic effects, and pharmacological approaches against protein misfolding diseases
Dillon J Rinauro, Fabrizio Chiti, Michele Vendruscolo, and Ryan Limbocker · 2024
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Proud: Pareto-guided diffusion model for multi-objective generation
Yinghua Yao, Yuangang Pan, Jing Li, Ivor Tsang, and Xin Yao · 2024
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Paretoflow: Guided flows in multi-objective optimization
Ye Yuan, Can Chen, Christopher Pal, and Xue Liu · 2024
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A continuous relaxation for discrete bayesian optimization
Richard Michael, Simon Bartels, Miguel González-Duque, Yevgen Zainchkovskyy, Jes Frellsen, Søren Hauberg, and Wouter Boomsma · 2024
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Simple and effective masked diffusion language models
Subham Sekhar Sahoo, Marianne Arriola, Yair Schiff, Aaron Gokaslan, Edgar Marroquin, Justin T Chiu, Alexander Rush, and Volodymyr Kuleshov · 2024
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Interpretation of allele-specific chromatin accessibility using cell state–aware deep learning
Zeynep Kalender Atak, Ibrahim Ihsan Taskiran, Jonas Demeulemeester, Christopher Flerin, David Mauduit, Liesbeth Minnoye, Gert Hulselmans, Valerie Christiaens, Ghanem-Elias Ghanem, Jasper Wouters, et al · 2021
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Peptherdia: database and structural composition analysis of approved peptide therapeutics and diagnostics
Vera D’Aloisio, Paolo Dognini, Gillian A Hutcheon, and Christopher R Coxon · 2021
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Toxinpred2: an improved method for predicting toxicity of proteins
Neelam Sharma, Leimarembi Devi Naorem, Shipra Jain, and Gajendra PS Raghava · 2022
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Pepnn: a deep attention model for the identification of peptide binding sites
Osama Abdin, Satra Nim, Han Wen, and Philip M Kim · 2022
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The toxicity of protein aggregates: new insights into the mechanisms, 2023
Alessandra Bigi, Eva Lombardo, Roberta Cascella, and Cristina Cecchi · 2023
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Learning to design protein-protein interactions with enhanced generalization
Anton Bushuiev, Roman Bushuiev, Petr Kouba, Anatolii Filkin, Marketa Gabrielova, Michal Gabriel, Jiri Sedlar, Tomas Pluskal, Jiri Damborsky, Stanislav Mazurenko, et al · 2023
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Evolutionary-scale prediction of atomic-level protein structure with a language model
Zeming Lin, Halil Akin, Roshan Rao, Brian Hie, Zhongkai Zhu, Wenting Lu, Nikita Smetanin, Robert Verkuil, Ori Kabeli, Yaniv Shmueli, et al · 2023
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Discrete flow matching
Itai Gat, Tal Remez, Neta Shaul, Felix Kreuk, Ricky TQ Chen, Gabriel Synnaeve, Yossi Adi, and Yaron Lipman · 2024
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Exploring discrete flow matching for 3d de novo molecule generation
Ian Dunn and David Ryan Koes · 2024
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Dirichlet flow matching with applications to dna sequence design
Hannes Stark, Bowen Jing, Chenyu Wang, Gabriele Corso, Bonnie Berger, Regina Barzilay, and Tommi Jaakkola · 2024
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Fisher flow matching for generative modeling over discrete data
Oscar Davis, Samuel Kessler, Mircea Petrache, Ismail Ceylan, Michael Bronstein, and Joey Bose · 2024
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Biolip2: an updated structure database for biologically relevant ligand–protein interactions
Chengxin Zhang, Xi Zhang, Peter L Freddolino, and Yang Zhang · 2024
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Accurate structure prediction of biomolecular interactions with alphafold 3
Josh Abramson, Jonas Adler, Jack Dunger, Richard Evans, Tim Green, Alexander Pritzel, Olaf Ronneberger, Lindsay Willmore, Andrew J Ballard, Joshua Bambrick, et al · 2024
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Admet-ai: a machine learning admet platform for evaluation of large-scale chemical libraries
Kyle Swanson, Parker Walther, Jeremy Leitz, Souhrid Mukherjee, Joseph C Wu, Rabindra V Shivnaraine, and James Zou · 2024
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Predicting dna structure using a deep learning method
Jinsen Li, Tsu-Pei Chiu, and Remo Rohs · 2024
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Thpdb2: compilation of fda approved therapeutic peptides and proteins
Shipra Jain, Srijanee Gupta, Sumeet Patiyal, and Gajendra PS Raghava · 2024
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Genome-wide crispr guide rna design and specificity analysis with guidescan2
Henri Schmidt, Minsi Zhang, Dimitar Chakarov, Vineet Bansal, Haralambos Mourelatos, Francisco J Sánchez-Rivera, Scott W Lowe, Andrea Ventura, Christina S Leslie, and Yuri Pritykin · 2025
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Neural network conditioned to produce thermophilic protein sequences can increase thermal stability
Evan Komp, Christian Phillips, Lauren M Lee, Shayna M Fallin, Humood N Alanzi, Marlo Zorman, Michelle E McCully, and David AC Beck · 2025
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Unlocking guidance for discrete state-space diffusion and flow models
Hunter Nisonoff, Junhao Xiong, Stephan Allenspach, and Jennifer Listgarten · 2025
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