Machine learning for metabolic engineering: A review

Can exascale computing and explainable artificial intelligence applied to plant biology deliver on the United Nations sustainable development goals?

(2020) Jared Streich et al.   CURRENT OPINION IN BIOTECHNOLOGY

Vector casting for noise reduction

(2020) Medhanie Tesfay Gebrekidan et al.   JOURNAL OF RAMAN SPECTROSCOPY

EvoBot: An Open-Source, Modular, Liquid Handling Robot for Scientific Experiments

(2020) Andres Faiña et al.   Applied Sciences-Basel

AMPL: A Data-Driven Modeling Pipeline for Drug Discovery

(2020) Amanda J. Minnich et al.   Journal of Chemical Information and Modeling

Predictive biology: modelling, understanding and harnessing microbial complexity

(2020) Allison J. Lopatkin et al.   NATURE REVIEWS MICROBIOLOGY

Model-driven generation of artificial yeast promoters

(2020) Benjamin J. Kotopka et al.   Nature Communications

Leveraging open hardware to alleviate the burden of COVID-19 on global health systems

(2020) Andre Maia Chagas et al.   PLOS BIOLOGY

Deep reinforcement learning for the control of microbial co-cultures in bioreactors

(2020) Neythen J. Treloar et al.   PLoS Computational Biology

Self-driving laboratory for accelerated discovery of thin-film materials

(2020) B. P. MacLeod et al.   Science Advances

Machine learning and ligand binding predictions: A review of data, methods, and obstacles

(2020) Sally R. Ellingson et al.   BIOCHIMICA ET BIOPHYSICA ACTA-GENERAL SUBJECTS

A mobile robotic chemist

(2020) Benjamin Burger et al.   NATURE

In vitro prototyping and rapid optimization of biosynthetic enzymes for cell design

(2020) Ashty S. Karim et al.   Nature Chemical Biology

A mechanism-aware and multiomic machine-learning pipeline characterizes yeast cell growth

(2020) Christopher Culley et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Biosystems Design by Machine Learning

(2020) Michael Jeffrey Volk et al.   ACS Synthetic Biology

A machine learning Automated Recommendation Tool for synthetic biology

(2020) Tijana Radivojević et al.   Nature Communications

Combining mechanistic and machine learning models for predictive engineering and optimization of tryptophan metabolism

(2020) Jie Zhang et al.   Nature Communications

SelProm: A Queryable and Predictive Expression Vector Selection Tool for Escherichia coli

(2019) Adrian J. Jervis et al.   ACS Synthetic Biology

Redirecting Metabolic Flux via Combinatorial Multiplex CRISPRi-Mediated Repression for Isopentenol Production in Escherichia coli

(2019) Tian Tian et al.   ACS Synthetic Biology

Diversifying the structure of zinc finger nucleases for high-precision genome editing

(2019) David E. Paschon et al.   Nature Communications

Engineering Robust Production Microbes for Large-Scale Cultivation

(2019) Maren Wehrs et al.   TRENDS IN MICROBIOLOGY

Systems Metabolic Engineering Strategies: Integrating Systems and Synthetic Biology with Metabolic Engineering

(2019) Kyeong Rok Choi et al.   TRENDS IN BIOTECHNOLOGY

DeepRibo: a neural network for precise gene annotation of prokaryotes by combining ribosome profiling signal and binding site patterns

(2019) Jim Clauwaert et al.   NUCLEIC ACIDS RESEARCH

SignalP 5.0 improves signal peptide predictions using deep neural networks

(2019) José Juan Almagro Armenteros et al.   NATURE BIOTECHNOLOGY

Complete biosynthesis of cannabinoids and their unnatural analogues in yeast

(2019) Xiaozhou Luo et al.   NATURE

Scientists brew cannabis using hacked beer yeast

(2019) Elie Dolgin   NATURE

AlphaFold at CASP13

(2019) Mohammed AlQuraishi   BIOINFORMATICS

Systems Metabolic Engineering Meets Machine Learning: A New Era for Data‐Driven Metabolic Engineering

(2019) Kristin V. Presnell et al.   Biotechnology Journal

A DIY approach to automating your lab

(2019) Mike May   NATURE

Prosit: proteome-wide prediction of peptide tandem mass spectra by deep learning

(2019) Siegfried Gessulat et al.   NATURE METHODS

RNAi expression tuning, microfluidic screening, and genome recombineering for improved protein production in Saccharomyces cerevisiae

(2019) Guokun Wang et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Machine learning-assisted directed protein evolution with combinatorial libraries

(2019) Zachary Wu et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Lessons from Two Design–Build–Test–Learn Cycles of Dodecanol Production in Escherichia coli Aided by Machine Learning

(2019) Paul Opgenorth et al.   ACS Synthetic Biology

DARPA’s Explainable Artificial Intelligence (XAI) Program

(2019) David Gunning et al.   AI MAGAZINE

Towards artificial general intelligence with hybrid Tianjic chip architecture

(2019) Jing Pei et al.   NATURE

Three pitfalls to avoid in machine learning

(2019) Patrick Riley   NATURE

Machine-learning-guided directed evolution for protein engineering

(2019) Kevin K. Yang et al.   NATURE METHODS

Massively parallel screening of synthetic microbial communities

(2019) Jared Kehe et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Deep learning enables high-quality and high-throughput prediction of enzyme commission numbers

(2019) Jae Yong Ryu et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Building a global alliance of biofoundries

(2019) Nathan Hillson et al.   Nature Communications

Opportunities at the Intersection of Synthetic Biology, Machine Learning, and Automation

(2019) Pablo Carbonell et al.   ACS Synthetic Biology

Machine and deep learning meet genome-scale metabolic modeling

(2019) Guido Zampieri et al.   PLoS Computational Biology

Automated “Cells-To-Peptides” Sample Preparation Workflow for High-Throughput, Quantitative Proteomic Assays of Microbes

(2019) Yan Chen et al.   JOURNAL OF PROTEOME RESEARCH

Common principles and best practices for engineering microbiomes

(2019) Christopher E. Lawson et al.   NATURE REVIEWS MICROBIOLOGY

Unified rational protein engineering with sequence-based deep representation learning

(2019) Ethan C. Alley et al.   NATURE METHODS

High‐accuracy protein structures by combining machine‐learning with physics‐based refinement

(2019) Lim Heo et al.   PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS

Towards a fully automated algorithm driven platform for biosystems design

(2019) Mohammad HamediRad et al.   Nature Communications

Deep Learning for the Precise Peak Detection in High-Resolution LC–MS Data

(2019) Arsenty D. Melnikov et al.   ANALYTICAL CHEMISTRY

Robotic Process Automation: Contemporary themes and challenges

(2019) Rehan Syed et al.   COMPUTERS IN INDUSTRY

Optimization of the IPP-bypass mevalonate pathway and fed-batch fermentation for the production of isoprenol in Escherichia coli

(2019) Aram Kang et al.   METABOLIC ENGINEERING

Reinforcement Learning for Bioretrosynthesis

(2019) Mathilde Koch et al.   ACS Synthetic Biology

XAI—Explainable artificial intelligence

(2019) David Gunning et al.   Science Robotics

Machine learning applications in systems metabolic engineering

(2019) Gi Bae Kim et al.   CURRENT OPINION IN BIOTECHNOLOGY

Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI

(2019) Alejandro Barredo Arrieta et al.   Information Fusion

Improved enzyme annotation with EC-specific cutoffs using DETECT v2

(2018) Nirvana Nursimulu et al.   BIOINFORMATICS

OUP accepted manuscript

(2018)   BIOINFORMATICS

A Novel Mammalian Cell Line Development Platform utilizing Nanofluidics and OptoElectro Positioning (OEP) technology

(2018) Kim Le et al.   BIOTECHNOLOGY PROGRESS

Robotic Process Automation

(2018) Wil M. P. van der Aalst et al.   Business & Information Systems Engineering

Computational fluid dynamics simulation of an industrial P. chrysogenum fermentation with a coupled 9-pool metabolic model: Towards rational scale-down and design optimization

(2018) Cees Haringa et al.   CHEMICAL ENGINEERING SCIENCE

The analytical process to search for metabolomics biomarkers

(2018) M.D. Luque de Castro et al.   JOURNAL OF PHARMACEUTICAL AND BIOMEDICAL ANALYSIS

RetroPath2.0: A retrosynthesis workflow for metabolic engineers

(2018) Baudoin Delépine et al.   METABOLIC ENGINEERING

MiYA, an efficient machine-learning workflow in conjunction with the YeastFab assembly strategy for combinatorial optimization of heterologous metabolic pathways in Saccharomyces cerevisiae

(2018) Yikang Zhou et al.   METABOLIC ENGINEERING

Genome-scale engineering of Saccharomyces cerevisiae with single-nucleotide precision

(2018) Zehua Bao et al.   NATURE BIOTECHNOLOGY

Deep learning improves prediction of CRISPR–Cpf1 guide RNA activity

(2018) Hui Kwon Kim et al.   NATURE BIOTECHNOLOGY

Precise, automated control of conditions for high-throughput growth of yeast and bacteria with eVOLVER

(2018) Brandon G Wong et al.   NATURE BIOTECHNOLOGY

Using deep learning to model the hierarchical structure and function of a cell

(2018) Jianzhu Ma et al.   NATURE METHODS

Iterative random forests to discover predictive and stable high-order interactions

(2018) Sumanta Basu et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Pathway design using de novo steps through uncharted biochemical spaces

(2018) Akhil Kumar et al.   Nature Communications

Industrial brewing yeast engineered for the production of primary flavor determinants in hopped beer

(2018) Charles M. Denby et al.   Nature Communications

SynBioHub: A Standards-Enabled Design Repository for Synthetic Biology

(2018) James Alastair McLaughlin et al.   ACS Synthetic Biology

Deep Learning for Computer Vision: A Brief Review

(2018) Athanasios Voulodimos et al.   Computational Intelligence and Neuroscience

EnzyNet: enzyme classification using 3D convolutional neural networks on spatial representation

(2018) Afshine Amidi et al.   PeerJ

Prediction of off-target activities for the end-to-end design of CRISPR guide RNAs

(2018) Jennifer Listgarten et al.   Nature Biomedical Engineering

ECPred: a tool for the prediction of the enzymatic functions of protein sequences based on the EC nomenclature

(2018) Alperen Dalkiran et al.   BMC BIOINFORMATICS

Planning chemical syntheses with deep neural networks and symbolic AI

(2018) Marwin H. S. Segler et al.   NATURE

CRISPR-Cas guides the future of genetic engineering

(2018) Gavin J. Knott et al.   SCIENCE

Chimera: enabling hierarchy based multi-objective optimization for self-driving laboratories

(2018) Florian Häse et al.   Chemical Science

Machine-Learning-Guided Mutagenesis for Directed Evolution of Fluorescent Proteins

(2018) Yutaka Saito et al.   ACS Synthetic Biology

Haves and have nots must find a better way: The case for open scientific hardware

(2018) Andre Maia Chagas   PLOS BIOLOGY

A Review of Dynamic Modeling Approaches and Their Application in Computational Strain Optimization for Metabolic Engineering

(2018) Osvaldo D. Kim et al.   Frontiers in Microbiology

Machine Learning Predicts the Yeast Metabolome from the Quantitative Proteome of Kinase Knockouts

(2018) Aleksej Zelezniak et al.   Cell Systems

Deep reinforcement learning for de novo drug design

(2018) Mariya Popova et al.   Science Advances

Deep scanning lysine metabolism in Escherichia coli

(2018) Marcelo C Bassalo et al.   Molecular Systems Biology

Five innovative ways to use 3D printing in the laboratory

(2018) Andrew Silver   NATURE

A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play

(2018) David Silver et al.   SCIENCE

Machine learning applied to enzyme turnover numbers reveals protein structural correlates and improves metabolic models

(2018) David Heckmann et al.   Nature Communications

Tuning the Performance of Synthetic Riboswitches using Machine Learning

(2018) Ann-Christin Groher et al.   ACS Synthetic Biology

Machine Learning of Designed Translational Control Allows Predictive Pathway Optimization in Escherichia coli

(2018) Adrian J. Jervis et al.   ACS Synthetic Biology

Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

(2018) M. Raissi et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Chromatin accessibility and guide sequence secondary structure affect CRISPR-Cas9 gene editing efficiency

(2017) Kristopher Torp Jensen et al.   FEBS LETTERS

Natural language processing systems for capturing and standardizing unstructured clinical information: A systematic review

(2017) Kory Kreimeyer et al.   JOURNAL OF BIOMEDICAL INFORMATICS

Droplet microfluidics for synthetic biology

(2017) Philip C. Gach et al.   LAB ON A CHIP

Engineering biological systems using automated biofoundries

(2017) Ran Chao et al.   METABOLIC ENGINEERING

REPARATION: ribosome profiling assisted (re-)annotation of bacterial genomes

(2017) Elvis Ndah et al.   NUCLEIC ACIDS RESEARCH

Automated multiplex genome-scale engineering in yeast

(2017) Tong Si et al.   Nature Communications

sgRNA Scorer 2.0: A Species-Independent Model To Predict CRISPR/Cas9 Activity

(2017) Raj Chari et al.   ACS Synthetic Biology

The Experiment Data Depot: A Web-Based Software Tool for Biological Experimental Data Storage, Sharing, and Visualization

(2017) William C. Morrell et al.   ACS Synthetic Biology

Open for business

(2017)   Scientific Data

Morphology and mechanics of fungal mycelium

(2017) M. R. Islam et al.   Scientific Reports

Engineering Cellular Metabolism

(2016) Jens Nielsen et al.   CELL

Euler-Lagrange computational fluid dynamics for (bio)reactor scale down: An analysis of organism lifelines

(2016) Cees Haringa et al.   ENGINEERING IN LIFE SCIENCES

iSCHRUNK – I n S ilico Approach to Ch aracterization and R eduction of Un certainty in the K inetic Models of Genome-scale Metabolic Networks

(2016) Stefano Andreozzi et al.   METABOLIC ENGINEERING

Mastering the game of Go with deep neural networks and tree search

(2016) David Silver et al.   NATURE

Genome-wide mapping of mutations at single-nucleotide resolution for protein, metabolic and genome engineering

(2016) Andrew D Garst et al.   NATURE BIOTECHNOLOGY

Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9

(2016) John G Doench et al.   NATURE BIOTECHNOLOGY

UniProt: the universal protein knowledgebase

(2016)   NUCLEIC ACIDS RESEARCH

Toward the First Data Acquisition Standard in Synthetic Biology

(2016) Iñaki Sainz de Murieta et al.   ACS Synthetic Biology

Semisupervised Gaussian Process for Automated Enzyme Search

(2016) Joseph Mellor et al.   ACS Synthetic Biology

Wet Lab Accelerator: A Web-Based Application Democratizing Laboratory Automation for Synthetic Biology

(2016) Maxwell Bates et al.   ACS Synthetic Biology

Rapid Prediction of Bacterial Heterotrophic Fluxomics Using Machine Learning and Constraint Programming

(2016) Stephen Gang Wu et al.   PLoS Computational Biology

Envelope filter sequence to delete blinks and overshoots

(2015) Manuel Merino et al.   Biomedical Engineering Online

The potential of random forest and neural networks for biomass and recombinant protein modeling inEscherichia colifed-batch fermentations

(2015) Michael Melcher et al.   Biotechnology Journal

Using Genome-scale Models to Predict Biological Capabilities

(2015) Edward J. O’Brien et al.   CELL

Screening and modular design for metabolic pathway optimization

(2015) Jason T Boock et al.   CURRENT OPINION IN BIOTECHNOLOGY

Genome scale engineering techniques for metabolic engineering

(2015) Rongming Liu et al.   METABOLIC ENGINEERING

Principal component analysis of proteomics (PCAP) as a tool to direct metabolic engineering

(2015) Jorge Alonso-Gutierrez et al.   METABOLIC ENGINEERING

Deep learning

(2015) Yann LeCun et al.   NATURE

MetaNetX/MNXref – reconciliation of metabolites and biochemical reactions to bring together genome-scale metabolic networks

(2015) Sébastien Moretti et al.   NUCLEIC ACIDS RESEARCH

PubChem Substance and Compound databases

(2015) Sunghwan Kim et al.   NUCLEIC ACIDS RESEARCH

BiGG Models: A platform for integrating, standardizing and sharing genome-scale models

(2015) Zachary A. King et al.   NUCLEIC ACIDS RESEARCH

Big Data: Astronomical or Genomical?

(2015) Zachary D. Stephens et al.   PLOS BIOLOGY

The potential of random forest and neural networks for biomass and recombinant protein modeling inEscherichia colifed-batch fermentations

(2015) Michael Melcher et al.   Biotechnology Journal

Metabolic engineering for the high-yield production of isoprenoid-based C5 alcohols in E. coli

(2015) Kevin W. George et al.   Scientific Reports

UniRef clusters: a comprehensive and scalable alternative for improving sequence similarity searches

(2014) B. E. Suzek et al.   BIOINFORMATICS

Mechanism and inhibition of 1-deoxy-d-xylulose-5-phosphate reductoisomerase

(2014) Andrew S. Murkin et al.   BIOORGANIC CHEMISTRY

Genome-Scale CRISPR-Mediated Control of Gene Repression and Activation

(2014) Luke A. Gilbert et al.   CELL

The automated lab

(2014) Erika Check Hayden   NATURE

ProteomeXchange provides globally coordinated proteomics data submission and dissemination

(2014) Juan A Vizcaíno et al.   NATURE BIOTECHNOLOGY

E-CRISP: fast CRISPR target site identification

(2014) Florian Heigwer et al.   NATURE METHODS

Semi-synthetic artemisinin: a model for the use of synthetic biology in pharmaceutical development

(2014) Chris J. Paddon et al.   NATURE REVIEWS MICROBIOLOGY

UniProt: a hub for protein information

(2014)   NUCLEIC ACIDS RESEARCH

The new frontier of genome engineering with CRISPR-Cas9

(2014) J. A. Doudna et al.   SCIENCE

Systematic Evaluation of Methods for Integration of Transcriptomic Data into Constraint-Based Models of Metabolism

(2014) Daniel Machado et al.   PLoS Computational Biology

Towards kinetic modeling of genome-scale metabolic networks without sacrificing stoichiometric, thermodynamic and physiological constraints

(2013) Anirikh Chakrabarti et al.   Biotechnology Journal

Time-Split Cross-Validation as a Method for Estimating the Goodness of Prospective Prediction.

(2013) Robert P. Sheridan   Journal of Chemical Information and Modeling

Genome-scale engineering for systems and synthetic biology

(2013) K. M. Esvelt et al.   Molecular Systems Biology

DNA targeting specificity of RNA-guided Cas9 nucleases

(2013) Patrick D Hsu et al.   NATURE BIOTECHNOLOGY

Navigating the protein fitness landscape with Gaussian processes

(2013) P. A. Romero et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Synthetic biology: from hype to impact

(2013) Timothy S. Gardner   TRENDS IN BIOTECHNOLOGY

Metabolic Engineering: Past and Future

(2013) Benjamin M. Woolston et al.   Annual Review of Chemical and Biomolecular Engineering

EFICAz2.5: application of a high-precision enzyme function predictor to 396 proteomes

(2012) Narendra Kumar et al.   BIOINFORMATICS

A Whole-Cell Computational Model Predicts Phenotype from Genotype

(2012) Jonathan R. Karr et al.   CELL

Enzyme Informatics

(2012) Rosanna G. Alderson et al.   CURRENT TOPICS IN MEDICINAL CHEMISTRY

An automated workflow for enhancing microbial bioprocess optimization on a novel microbioreactor platform

(2012) Peter Rohe et al.   Microbial Cell Factories

Microbial engineering for the production of advanced biofuels

(2012) Pamela P. Peralta-Yahya et al.   NATURE

FLASH assembly of TALENs for high-throughput genome editing

(2012) Deepak Reyon et al.   NATURE BIOTECHNOLOGY

Design, implementation and practice of JBEI-ICE: an open source biological part registry platform and tools

(2012) T. S. Ham et al.   NUCLEIC ACIDS RESEARCH

MetaboLights—an open-access general-purpose repository for metabolomics studies and associated meta-data

(2012) Kenneth Haug et al.   NUCLEIC ACIDS RESEARCH

In silico method for modelling metabolism and gene product expression at genome scale

(2012) Joshua A. Lerman et al.   Nature Communications

Mathematical modeling of gene expression: a guide for the perplexed biologist

(2011) Ahmet Ay et al.   CRITICAL REVIEWS IN BIOCHEMISTRY AND MOLECULAR BIOLOGY

Cell-free synthetic biology: Thinking outside the cell

(2011) C. Eric Hodgman et al.   METABOLIC ENGINEERING

An integrated approach to characterize genetic interaction networks in yeast metabolism

(2011) Balázs Szappanos et al.   NATURE GENETICS

Gene prediction with Glimmer for metagenomic sequences augmented by classification and clustering

(2011) David R. Kelley et al.   NUCLEIC ACIDS RESEARCH

HMMER web server: interactive sequence similarity searching

(2011) R. D. Finn et al.   NUCLEIC ACIDS RESEARCH

From cloud computing to cloud manufacturing

(2011) Xun Xu   ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING

The role of metabolites and metabolomics in clinically applicable biomarkers of disease

(2010) Mamas Mamas et al.   ARCHIVES OF TOXICOLOGY

Molecular signatures-based prediction of enzyme promiscuity

(2010) Pablo Carbonell et al.   BIOINFORMATICS

Hybrid dynamic modeling of Escherichia coli central metabolic network combining Michaelis–Menten and approximate kinetic equations

(2010) Rafael S. Costa et al.   BIOSYSTEMS

A protocol for generating a high-quality genome-scale metabolic reconstruction

(2010) Ines Thiele et al.   Nature Protocols

GenBank

(2010) D. A. Benson et al.   NUCLEIC ACIDS RESEARCH

Predicting strength and function for promoters of the Escherichia coli alternative sigma factor,  E

(2010) V. A. Rhodius et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Isoprenoid Pathway Optimization for Taxol Precursor Overproduction in Escherichia coli

(2010) P. K. Ajikumar et al.   SCIENCE

Hidden Markov Models and their Applications in Biological Sequence Analysis

(2009) Byung-Jun Yoon   CURRENT GENOMICS

A Survey on Transfer Learning

(2009) Sinno Jialin Pan et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Automated design of synthetic ribosome binding sites to control protein expression

(2009) Howard M Salis et al.   NATURE BIOTECHNOLOGY

Genome-wide enzyme annotation with precision control: Catalytic families (CatFam) databases

(2008) Chenggang Yu et al.   PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS

Mining bioprocess data: opportunities and challenges

(2008) Salim Charaniya et al.   TRENDS IN BIOTECHNOLOGY