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Periodicals

Artificial intelligence-aided protein engineering: from topological data analysis to deep protein language models

Protein engineering is an emerging field in biotechnology that has the potential to revolutionize various areas, such as antibody design, drug discovery, food security, ecology, and more. However, the mutational space involved is too vast to be handled through experimental means alone. Leveraging accumulative protein databases, machine learning (ML) models, particularly those based on natural language processing (NLP), have considerably expedited protein engineering. Moreover, advances in topological data analysis (TDA) and artificial intelligence-based protein structure prediction, such as AlphaFold2, have made more powerful structure-based ML-assisted protein engineering strategies possible. This review aims to offer a comprehensive, systematic, and indispensable set of methodological components, including TDA and NLP, for protein engineering and to facilitate their future development.

Biotechnology• 2023• arXiv
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Periodicals

Theory of Reciprocating Contact for Viscoelastic Solids

A theory of reciprocating contacts for linear viscoelastic materials is presented. Results are discussed for the case of a rigid sphere sinusoidally driven in sliding contact with a viscoelastic half-space. Depending on the size of the contact, the frequency and amplitude of the reciprocating motion, and on the relaxation time of the viscoelastic body, we establish that the contact behavior may range from the steady-state viscoelastic solution, in which traction forces always oppose the direction of the sliding rigid punch, to a more elaborate trend, never observed before, which is due to the strong interaction between different regions of the path covered during the reciprocating motion. Practical implications span a number of applications, ranging from seismic engineering to biotechnology.

Biotechnology• 2016• arXiv
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Periodicals

Citation of scientific evidence from video description and its association with attention and impact

This study investigates how YouTube content creators utilize scientific evidence in videos. Log-linear regression examines the influence of alternative communication channels on video creators in Biotechnology, using data from 81,302 papers (2018-2023). This reveals a positive association with news articles and Wikipedia pages, but a negative association with scientific papers, policy documents, and patents. Despite the potential for enriching discussions, science video creators seem to favor materials with wider public attention over influential science, technology, and policy papers. These findings suggest a need for improved dissemination strategies for scientific research. Authors, universities, and journals should consider how their work can be made more accessible and engaging for science communicators on video.

Biotechnology• 2026• arXiv
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Periodicals

Physical Principles of Quantum Biology

This technical monograph provides a comprehensive overview of the field of quantum biology. It approaches quantum biology from a physical perspective with core quantum mechanical concepts presented foremost to provide a theoretical foundation for the field. An extensive body of research is covered to clarify the significance of quantum biology as a scientific field, outlining the field's long-standing importance in the historical development of quantum theory. This lays the essential groundwork to enable further advances in nanomedicine and biotechnology. Written for academics, biological science researchers, physicists, biochemists, medical technologists, and students of quantum mechanics, this text brings clarity to fundamental advances being made in the emerging science of quantum biology.

Biotechnology• 2025• arXiv
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Periodicals

Model Validation and Selection in Metabolic Flux Analysis and Flux Balance Analysis

13C-Metabolic Flux Analysis (13C-MFA) and Flux Balance Analysis (FBA) are widely used to investigate the operation of biochemical networks in both biological and biotechnological research. Both of these methods use metabolic reaction network models of metabolism operating at steady state, so that reaction rates (fluxes) and the levels of metabolic intermediates are constrained to be invariant. They provide estimated (MFA) or predicted (FBA) values of the fluxes through the network in vivo, which cannot be measured directly. A number of approaches have been taken to test the reliability of estimates and predictions from constraint-based methods and to decide on and/or discriminate between alternative model architectures. Despite advances in other areas of the statistical evaluation of metabolic models, validation and model selection methods have been underappreciated and underexplored. We review the history and state-of-the-art in constraint-based metabolic model validation and model selection. Applications and limitations of the X2-test of goodness-of-fit, the most widely used quantitative validation and selection approach in 13C-MFA, are discussed, and complementary and alternative forms of validation and selection are proposed. A combined model validation and selection framework for 13C-MFA incorporating metabolite pool size information that leverages new developments in the field is presented and advocated for. Finally, we discuss how the adoption of robust validation and selection procedures can enhance confidence in constraint-based modeling as a whole and ultimately facilitate more widespread use of FBA in biotechnology in particular.

Biotechnology• 2023• arXiv
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Periodicals

Representing Semantified Biological Assays in the Open Research Knowledge Graph

In the biotechnology and biomedical domains, recent text mining efforts advocate for machine-interpretable, and preferably, semantified, documentation formats of laboratory processes. This includes wet-lab protocols, (in)organic materials synthesis reactions, genetic manipulations and procedures for faster computer-mediated analysis and predictions. Herein, we present our work on the representation of semantified bioassays in the Open Research Knowledge Graph (ORKG). In particular, we describe a semantification system work-in-progress to generate, automatically and quickly, the critical semantified bioassay data mass needed to foster a consistent user audience to adopt the ORKG for recording their bioassays and facilitate the organisation of research, according to FAIR principles.

Biotechnology• 2020• arXiv
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Periodicals

Effects of Monovalent and Divalent Cations on the Rheology of Entangled DNA

In this paper we investigate the effects of varying cation valency and concentration on the rheology of entangled lambda DNA solutions. We show that monovalent cations moderately increase the viscoelasticty of the solutions mainly by stabilising linear condensation of lambda DNA ``monomers'' via hybridisation of their sticky ends. On the contrary, divalent cations have a far more complex and dramatic effect on the rheology of the solution and we observe evidence of inter-molecular DNA-DNA bridging by Mg2+. We argue that these results may be interesting in the context of dense solutions of single and double stranded DNA, e.g. in vivo or in biotechnology applications such as DNA origami and DNA hydrogels.

Biotechnology• 2023• arXiv
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Periodicals

Internet of Nano, Bio-Nano, Biodegradable and Ingestible Things: A Survey

In recent years, advances in biotechnology, nanotechnology and materials science have led to development of revolutionizing applications in Internet of Things (IoT). In particular, the interconnection of nanomaterials, nanoimplants and nanobiosensors with existing IoT networks have inspired the concepts of Internet of Nano Things (IoNT), Internet of Bio-Nano Things (IoBNT), Internet of Biodegradable Things (IoBDT) and Internet of Ingestible Things (IoIT). To date, although there are several survey papers that addressed these concepts separately, there is no current survey covering all studies in IoNT, IoBNT, IoBDT and IoIT. Therefore, in this paper, we provide a complete overview of all recent work in these four areas. Furthermore, we emphasize the research challenges, potential applications, and open research areas.

Biotechnology• 2022• arXiv
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Periodicals

Effective charge, collapse and the critical point of a polyelectrolyte chain

The charge of a polyelectrolyte (PE) controls myriads of phenomena in biology, biotechnology, and materials science, but still remains elusive from an understanding. Considering the adsorption of counterions on an isolated PE chain, an analytical expression for the effective charge - valid for all chain flexibility, for variable salt, in good solvents at all conditions, in poor solvents in the expanded (coil) state away from the critical point, and for gels, brushes and other PE systems in their expanded state - is derived. Phase boundaries and the critical point for the I-st order collapse transition, induced cooperatively by counterion adsorption and chain conformations, are calculated self-consistently. The size of the PE chain is found to be a single-valued function of charge.

Biotechnology• 2009• arXiv
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Periodicals

A Polymer Blend Substrate for Skeletal Muscle Cells Alignment and Photostimulation

Substrate engineering for steering cell growth is a wide and well-established area of research in the field of modern biotechnology. Here we introduce a micromachining technique to pattern an inert, transparent polymer matrix blended with a photoactive polymer. We demonstrate that the obtained scaffold combines the capability to align with that to photostimulate living cells. This technology can open up new and promising applications, especially where cell alignment is required to trigger specific biological functions, e.g. generate powerful and efficient muscle contractions following an external stimulus.

Biotechnology• 2020• arXiv
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Periodicals

Optimal Sparse Survival Trees

Interpretability is crucial for doctors, hospitals, pharmaceutical companies and biotechnology corporations to analyze and make decisions for high stakes problems that involve human health. Tree-based methods have been widely adopted for survival analysis due to their appealing interpretablility and their ability to capture complex relationships. However, most existing methods to produce survival trees rely on heuristic (or greedy) algorithms, which risk producing sub-optimal models. We present a dynamic-programming-with-bounds approach that finds provably-optimal sparse survival tree models, frequently in only a few seconds.

Biotechnology• 2024• arXiv
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Periodicals

Computational design of intrinsically disordered proteins

Protein design has the potential to revolutionize biotechnology and medicine. While most efforts have focused on proteins with well-defined structures, increased recognition of the functional significance of intrinsically disordered regions, together with improvements in their modeling, has paved the way to their computational de novo design. This review summarizes recent advances in engineering intrinsically disordered regions with tailored conformational ensembles, molecular recognition, and phase behavior. We discuss challenges in combining models with predictive accuracy with scalable design workflows and outline emerging strategies that integrate knowledge-based, physics-based, and machine-learning approaches.

Biotechnology• 2025• arXiv
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Periodicals

Prediction of the Economic Behavior of Fishery Biotechnology Companies Based on Machine Learning-Based Deep Metacellular Automata

Ocean warming significantly affects the fishing industry, with species like Scottish herring and mackerel migrating northwards. Our research, a fusion of artificial intelligence, data science, and operations research, addresses this crisis. Using Long Short Term Memory networks, we forecast sea surface temperatures (SST) and model fish migratory patterns with Enhanced Cellular Automata. A corrective factor within our model adjusts for human impact on SST, guiding diverse mitigation scenarios. We apply operational research to strategize responses, including the modernization of fishing vessels as a less costly alternative to relocation. Our data-driven approach, suggesting fleet modernization, strategic relocation, and product diversification, offers an effective approach to mitigating the threats to the ocean warming phenomenon.

Biotechnology• 2024• arXiv
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Periodicals

Quantitative measurement of the magnetic moment of an individual magnetic nanoparticle by magnetic force microscopy

We demonstrate the quantitative measurement of the magnetization of individual magnetic nanoparticles (MNP) using a magnetic force microscope (MFM). The quantitative measurement is realized by calibration of the MFM signal using an MNP reference sample with traceably determined magnetization. A resolution of the magnetic moment of the order of 10^(-18) Am^2 under ambient conditions is demonstrated which is presently limited by the tip's magnetic moment and the noise level of the instrument. The calibration scheme can be applied to practically any MFM and tip thus allowing a wide range of future applications e.g. in nanomagnetism and biotechnology.

Biotechnology• 2010• arXiv
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Periodicals

Automated Quantification of the Impact of the Wood-decay fungus Physisporinus vitreus on the Cell Wall Structure of Norway spruce by Tomographic Microscopy

Wood-decay fungi decompose their substrate by extracellular, degradative enzymes and play an important role in natural ecosystems by recycling carbon and minerals fixed in plants. Thereby, they cause significant damage to the wood structure and limit the use of wood as building material. Besides their role as biodeteriorators wood-decay fungi can be used for biotechnological purposes, e.g. the white-rot fungus Physisporinus vitreus for improving the uptake of preservatives and wood-modification substances of refractory wood. Therefore, the visualization and the quantification of microscopic decay patterns are important for the study of the impact of wood-decay fungi in general, as well as for wood-decay fungi and microorganisms with possible applications in biotechnology. In the present work, we developed a method for the automated localization and quantification of microscopic cell wall elements (CWE) of Norway spruce wood such as bordered pits, intrinsic defects, hyphae or alterations induced by P. vitreus using high resolution X-ray computed tomographic microscopy. In addition to classical destructive wood anatomical methods such as light or laser scanning microscopy, our method allows for the first time to compute the properties (e.g. area, orientation and size-distribution) of CWE of the tracheids in a sample. This is essential for modeling the influence of microscopic CWE to macroscopic properties such as wood strength and permeability.

Biotechnology• 2011• arXiv
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Periodicals

Reconstruction of Network Evolutionary History from Extant Network Topology and Duplication History

Genome-wide protein-protein interaction (PPI) data are readily available thanks to recent breakthroughs in biotechnology. However, PPI networks of extant organisms are only snapshots of the network evolution. How to infer the whole evolution history becomes a challenging problem in computational biology. In this paper, we present a likelihood-based approach to inferring network evolution history from the topology of PPI networks and the duplication relationship among the paralogs. Simulations show that our approach outperforms the existing ones in terms of the accuracy of reconstruction. Moreover, the growth parameters of several real PPI networks estimated by our method are more consistent with the ones predicted in literature.

Biotechnology• 2012• arXiv
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Periodicals

On the Emerging Area of Biocybersecurity and Relevant Considerations

Biocybersecurity is a novel space for the 21st century that meets our innovations in biotechnology and computing head on. Within this space, many considerations are open for and demand consideration as groups endeavor to develop products and policies that adequately ensure asset management and protection. Herein, simplified and brief exploration is given followed by some surface discussion of impacts. These impacts concern the end user, ethical and legal considerations, international proceedings, business, and limitations. It is hoped that this will be helpful in future considerations towards biocybersecurity policy developments and implementations. Notice: This article has been queued for publication in the Proceedings of the 2020 Future of Information and Communication Conference (FICC)

Biotechnology• 2020• arXiv
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Periodicals

A Two-Step Concept-Based Approach for Enhanced Interpretability and Trust in Skin Lesion Diagnosis

The main challenges hindering the adoption of deep learning-based systems in clinical settings are the scarcity of annotated data and the lack of interpretability and trust in these systems. Concept Bottleneck Models (CBMs) offer inherent interpretability by constraining the final disease prediction on a set of human-understandable concepts. However, this inherent interpretability comes at the cost of greater annotation burden. Additionally, adding new concepts requires retraining the entire system. In this work, we introduce a novel two-step methodology that addresses both of these challenges. By simulating the two stages of a CBM, we utilize a pretrained Vision Language Model (VLM) to automatically predict clinical concepts, and an off-the-shelf Large Language Model (LLM) to generate disease diagnoses based on the predicted concepts. Furthermore, our approach supports test-time human intervention, enabling corrections to predicted concepts, which improves final diagnoses and enhances transparency in decision-making. We validate our approach on three skin lesion datasets, demonstrating that it outperforms traditional CBMs and state-of-the-art explainable methods, all without requiring any training and utilizing only a few annotated examples. The code is available at https://github.com/CristianoPatricio/2-step-concept-based-skin-diagnosis.

Biotechnology• 2024• arXiv
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Periodicals

Enhanced Diffusion and Chemotaxis of Enzymes

Many enzymes appear to diffuse faster in the presence of substrate and to drift either up or down a concentration gradient of their substrate. Observations of these phenomena, termed enhanced enzyme diffusion (EED) and enzyme chemotaxis, respectively, lead to a novel view of enzymes as active matter. Enzyme chemotaxis and EED may be important in biology, and they could have practical applications in biotechnology and nanotechnology. They also are of considerable biophysical interest; indeed, their physical mechanisms are still quite uncertain. This review provides an analytic summary of experimental studies of these phenomena and of the mechanisms that have been proposed to explain them, and offers a perspective of future directions for the field.

Biotechnology• 2019• arXiv
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Periodicals

Chemical nanomachining of silicon by gold-catalyzed oxidation

A chemical nanomachining process for the rapid, scalable production of nanostructure assemblies from silicon-on-insulator is demonstrated. The process is based on the spontaneous, local oxidation of Si induced by Au, which is selectively evaporated onto the Si surface. The Au-catalyzed oxide forms a pattern that serves as a robust mask for the underlying Si, enabling the use of simple wet chemistry to sculpt arrays of nanostructures of diverse shapes including rings, pillars, wires, and nanopores. The remarkable simplicity of this chemical nanomachining process makes it widely accessible as an enabling technique for applications from photonics to biotechnology.

Biotechnology• 2007• arXiv
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Periodicals

CRISPR SWAPnDROP -- A multifunctional system for genome editing and large-scale interspecies gene transfer

The need for diverse chromosomal modifications in biotechnology, synthetic biology and basic research requires the development of new technologies. With CRISPR SWAPnDROP, we extend the limits of genome editing to large-scale in-vivo DNA transfer between bacterial species. Its modular platform approach facilitates species specific adaptation to confer genome editing in various species. In this study, we show the implementation of the CRISPR SWAPnDROP concept for the model organism Escherichia coli and the currently fastest growing and biotechnologically relevant organism Vibrio natriegens. We demonstrate the excision, transfer and integration of 151kb chromosomal DNA between E. coli strains and from E. coli to V. natriegens without size-limiting intermediate DNA extraction. With the transfer of the E. coli MG1655 wild type lac operon, we establish a functional lactose and galactose degradation pathway in V. natriegens to extend its biotechnological spectrum. We also transfer the E. coli DH5alpha lac operon and make V. natriegens capable of alpha-complementation - a step towards an ultra-fast cloning strain. Furthermore, CRISPR SWAPnDROP is designed to be the swiss army knife of genome engineering. Its spectrum of application comprises scarless, marker-free, iterative and parallel insertions and deletions, genome rearrangements, as well as gene transfer between strains and across species. The modular character facilitates DNA library applications and the recycling of standardized parts. Its novel multi-color scarless co-selection system significantly improves editing efficiency to 92% for single edits and 83% for quadruple edits and provides visual quality controls throughout the assembly and editing process.

Biotechnology• 2021• arXiv
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Periodicals

Conditionally unutilized proteins and their profound effects on growth and adaptation across microbial species

Protein synthesis is an important determinant of microbial growth and response that demands a high amount of metabolic and biosynthetic resources. Despite these costs, microbial species from different taxa and habitats massively synthesize proteins that are not utilized in the conditions they currently experience. Based on resource allocation models, recent studies have begun to reconcile the costs and benefits of these conditionally unutilized proteins (CUPs) in the context of varying environmental conditions. Such massive synthesis of CUPs is crucial to consider in different areas of modern microbiology, from the systematic investigation of cell physiology, via the prediction of evolution in laboratory and natural environments, to the rational design of strains in biotechnology applications.

Biotechnology• 2023• arXiv
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Periodicals

Melting Transition of Directly-Linked Gold Nanoparticle DNA Assembly

DNA melting and hybridization is a fundamental biological process as well as a crucial step in many modern biotechnology applications. DNA confined on surfaces exhibits different behavior from that in free solutions. The system of DNA-capped gold nanoparticles exhibits unique phase transitions and represents a new class of complex fluids. Depending on the sequence of the DNA, particles can be linked to each other through direct complementary DNA sequences or via a ``linker'' DNA whose sequence is complementary to the sequence attached to the gold nanoparticles. We observed different melting transitions for these two distinct systems.

Biotechnology• 2005• arXiv
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Review times in peer review: quantitative analysis of editorial workflows

We examine selected aspects of peer review and suggest possible improvements. To this end, we analyse a dataset containing information about 300 papers submitted to the Biochemistry and Biotechnology section of the Journal of the Serbian Chemical Society. After separating the peer review process into stages that each review has to go through, we use a weighted directed graph to describe it in a probabilistic manner and test the impact of some modifications of the editorial policy on the efficiency of the whole process.

Biotechnology• 2015• arXiv
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