Nature Biotechnology

Aims & Scope

Nature Biotechnology is a monthly journal covering the science and business of biotechnology. It publishes new concepts in technology/methodology of relevance to the biological, biomedical, agricultural and environmental sciences as well as covers the commercial, political, ethical, legal, and societal aspects of this research. The first function is fulfilled by the peer-reviewed research section, the second by the expository efforts in the front of the journal. We provide researchers with news about business; we provide the business community with news about research developments. The core areas in which we are actively seeking research papers include: molecular engineering of nucleic acids and proteins; molecular therapy (therapeutics genes, antisense, siRNAs, aptamers, DNAzymes, ribozymes, peptides, proteins); large-scale biology (genomics, functional genomics, proteomics, structural genomics, metabolomics, etc.); computational biology (algorithms and modeling), regenerative medicine (stem cells, tissue engineering, biomaterials); imaging technology; analytical biotechnology (sensors/detectors for analytes/macromolecules), applied immunology (antibody engineering, xenotransplantation, T-cell therapies); food and agricultural biotechnology; and environmental biotechnology. A comprehensive list of areas of interest is shown below. Genetic engineering Strategies for controlling gene expression Strategies for manipulating gene structure Strategies for gene containment Large-scale approaches Technologies for analyzing gene function (e.g., arrays, SAGE) Technologies for analyzing gene structure/organization (e.g., molecular beacons) Chemogenomics or chemical genetics Pharmacogenomics/SNPs Computational analysis Proteomics Technologies for analyzing/identifying protein structure/function (e.g., 2-D gels, mass spectrometry, yeast two-hybrid, SPR, NMR, arrays and chips) Structural genomics Computational analysis Metabolomics Technologies for analyzing/profiling metabolites (chromatography, mass spectrometry) Computational analysis Computational biology Bioinformatics; algorithms; data deconvolution Modeling and systems biology: kinetics-based models and constraints-based models Molecular engineering Rational approaches for proteins/antibodies/enzymes/drugs Molecular evolution Molecular breeding approaches Metabolic engineering Genetic manipulation of species of interest to modify or allow the production of a commercially or therapeutically relevant compound Computational analysis Novel expression systems Mammalian cells Insect cells Bacteria Fungi Plant cells Delivery of genes, drugs, or cells Targeting strategies Viral and nonviral vector strategies Imaging Reporter molecules Imaging approaches/technologies for visualizing whole animals, cells, or single molecules Computational analysis Nucleic acid therapeutics Gene therapy (targeting, expression, integration, immunogenicity) Antisense RNAi DNAzymes and ribozymes Other (e.g., chimeric oligonucleotides/triple helix) Nanobiotechnology Nanomaterials for use in drug delivery or as therapeutics Nanomaterials for use in industrial biotechnology Nanosensors Nanosystems for imaging molecules and cells Vaccines and applied immunology Antibody engineering T-cell therapies Therapies exploiting innate immunity (e.g. complement) Antigen delivery vectors and approaches Nucleic acid vaccines Computational analysis Regenerative medicine Stem cells Tissue engineering Therapeutic cloning (somatic cell nuclear transfer) Xenotransplantation Biomaterials Biosensors Approaches for detecting biological molecules Use of biological systems in detecting analytes Assay systems Approaches for multiplexing and increasing throughput Selection/screening strategies for gene/proteins/drugs Microfluidics Biomaterials Engineering materials for biological application Molecular imprinting Biomimetics Nanotechnology Agbiotech and transgenic plants Crop improvement (resis

Based on the Think.Check.Submit framework by DOAJ, COPE & OASPA. All data from verified open sources.

Source: OpenAlex · Each year’s green bar = citations earned by that year’s papers, counted to date — so recent years look lower simply because their papers haven’t had time to be cited yet.

SJR Quartile by Discipline

Scimago ranks this journal separately in each subject category — its quartile can differ by discipline.

Subject Classification