Academic Digital Library for institutions, students, and solo learners

Discovery

Content search and filters

This is the first search surface for the seven content types. Next we will connect full-text search and metadata-specific filters.

Results 1,892

Periodicals

De novo design of high-affinity protein binders with AlphaProteo

Computational design of protein-binding proteins is a fundamental capability with broad utility in biomedical research and biotechnology. Recent methods have made strides against some target proteins, but on-demand creation of high-affinity binders without multiple rounds of experimental testing remains an unsolved challenge. This technical report introduces AlphaProteo, a family of machine learning models for protein design, and details its performance on the de novo binder design problem. With AlphaProteo, we achieve 3- to 300-fold better binding affinities and higher experimental success rates than the best existing methods on seven target proteins. Our results suggest that AlphaProteo can generate binders "ready-to-use" for many research applications using only one round of medium-throughput screening and no further optimization.

Biotechnology• 2024• arXiv
Access Full TextView Details
Periodicals

Biophysical EPR Using Superconducting Resonators

We present innovations that enable the use of superconducting resonators for high sensitivity, high bandwidth pulsed electron paramagnetic resonance (EPR) measurements on biologically relevant samples with enhanced stability and throughput. A custom-built X-band pulsed EPR spectrometer with AWG and digital IF capability generated by an FPGA was used to control a novel patterned thin film planar superconducting microstrip resonator capable of generating Rabi fields sufficient to achieve 6 ns pi/2 Gaussian pulses using a 100 W solid-state HPA. The system allows automated sequential calibration, measurement, and analysis of five 3.5 uL samples contained in a sample cartridge. Performance was validated through measurements of double electron-electron resonance (DEER) distances in a variety of spin-labeled protein samples with biologically relevant concentrations, including measurements below 10 uM. The results enable broadening the scope of applications for both superconducting resonators and the use of EPR in biotechnology.

Biotechnology• 2026• arXiv
Access Full TextView Details
Periodicals

Identification of New Assembly Mode in the Heliconical Nematic Phase via Tender Resonant X-ray Scattering

Helical structures are exciting and are utilized in numerous applications ranging from biotechnology to displays to medicine. Accurate description and understanding of resonance effects in helical structures provides crucial knowledge on molecular packing beyond positional ordering. We exam-ined the manifestation of resonance effects in a nematic phase with heliconical structure, the so called twist bend nematic (NTB) via tender resonant X-ray scattering (TReXS) at the sulfur K-edge. We demonstrate for the first time quantitatively that the energy dependence of the scattering peak in the NTB phase follows the energy dependence of the complex refractive indices measured by X-ray absorption. This allows us to identify a new self-assembly mode for specific sets of liquid crystal dimers in the NTB phase. We anticipate that new avenues in the exploration of complex orientational structures both in static as well as in dynamic modes induced by external stimuli will be pursued.

Biotechnology• 2019• arXiv
Access Full TextView Details
Periodicals

Maximum Cliques in Protein Structure Comparison

Computing the similarity between two protein structures is a crucial task in molecular biology, and has been extensively investigated. Many protein structure comparison methods can be modeled as maximum clique problems in specific k-partite graphs, referred here as alignment graphs. In this paper, we propose a new protein structure comparison method based on internal distances (DAST) which is posed as a maximum clique problem in an alignment graph. We also design an algorithm (ACF) for solving such maximum clique problems. ACF is first applied in the context of VAST, a software largely used in the National Center for Biotechnology Information, and then in the context of DAST. The obtained results on real protein alignment instances show that our algorithm is more than 37000 times faster than the original VAST clique solver which is based on Bron & Kerbosch algorithm. We furthermore compare ACF with one of the fastest clique finder, recently conceived by Ostergard. On a popular benchmark (the Skolnick set) we observe that ACF is about 20 times faster in average than the Ostergard's algorithm.

Biotechnology• 2009• arXiv
Access Full TextView Details
Periodicals

Green-extraction of carbon thin films from natural mineral Shungite

Conventional fabrication methods to produce graphene are cumbersome, expensive and are not ecology friendly. This is due to the fact that a large volume of raw materials requires a large number of acids and alkalis, which in turn requires special disposal. Therefore, it is necessary to develop new technologies or refine existing technologies for the production of graphene and create new ecology-safe and effective methods to produce graphene. Here, we utilized the physical dispergation to extract graphene films from natural mineral shungite rock. We studied the structure of shungite via Raman spectrometry and X-ray phases analysis and found that the shungite refers to graphite-like mineral structures. From spectral data, we learned that the main constituent of shungite is amorphous carbon in sp2 and sp3 forms. Transmission electron microscopy images of the processed material revealed that the obtained graphene films with well-developed surfaces are as small as 200 nanometers. Our green fabrication method of graphene can be widely used in a variety of fields from electronics (electrodes), optics, biotechnology (biosensors), ecology (sorbents for wastewater, air purification) to list a few.

Biotechnology• 2021• arXiv
Access Full TextView Details
Periodicals

Utilising Graph Machine Learning within Drug Discovery and Development

Graph Machine Learning (GML) is receiving growing interest within the pharmaceutical and biotechnology industries for its ability to model biomolecular structures, the functional relationships between them, and integrate multi-omic datasets - amongst other data types. Herein, we present a multidisciplinary academic-industrial review of the topic within the context of drug discovery and development. After introducing key terms and modelling approaches, we move chronologically through the drug development pipeline to identify and summarise work incorporating: target identification, design of small molecules and biologics, and drug repurposing. Whilst the field is still emerging, key milestones including repurposed drugs entering in vivo studies, suggest graph machine learning will become a modelling framework of choice within biomedical machine learning.

Biotechnology• 2020• arXiv
Access Full TextView Details
Periodicals

Encoding protein dynamic information in graph representation for functional residue identification

Recent advances in protein function prediction exploit graph-based deep learning approaches to correlate the structural and topological features of proteins with their molecular functions. However, proteins in vivo are not static but dynamic molecules that alter conformation for functional purposes. Here we apply normal mode analysis to native protein conformations and augment protein graphs by connecting edges between dynamically correlated residue pairs. In the multilabel function classification task, our method demonstrates a remarkable performance gain based on this dynamics-informed representation. The proposed graph neural network, ProDAR, increases the interpretability and generalizability of residue-level annotations and robustly reflects structural nuance in proteins. We elucidate the importance of dynamic information in graph representation by comparing class activation maps for hMTH1, nitrophorin, and SARS-CoV-2 receptor binding domain. Our model successfully learns the dynamic fingerprints of proteins and pinpoints the residues of functional impacts, with vast untapped potential for broad biotechnology and pharmaceutical applications.

Biotechnology• 2021• arXiv
Access Full TextView Details
Periodicals

Improving Protein Optimization with Smoothed Fitness Landscapes

The ability to engineer novel proteins with higher fitness for a desired property would be revolutionary for biotechnology and medicine. Modeling the combinatorially large space of sequences is infeasible; prior methods often constrain optimization to a small mutational radius, but this drastically limits the design space. Instead of heuristics, we propose smoothing the fitness landscape to facilitate protein optimization. First, we formulate protein fitness as a graph signal then use Tikunov regularization to smooth the fitness landscape. We find optimizing in this smoothed landscape leads to improved performance across multiple methods in the GFP and AAV benchmarks. Second, we achieve state-of-the-art results utilizing discrete energy-based models and MCMC in the smoothed landscape. Our method, called Gibbs sampling with Graph-based Smoothing (GGS), demonstrates a unique ability to achieve 2.5 fold fitness improvement (with in-silico evaluation) over its training set. GGS demonstrates potential to optimize proteins in the limited data regime. Code: https://github.com/kirjner/GGS

Biotechnology• 2023• arXiv
Access Full TextView Details
Periodicals

Molecular gates in mesoporous bioactive glasses for the treatment of bone tumors and infection

Silica mesoporous nanomaterials have been proved to have meaningful application in biotechnology and biomedicine. Particularly, mesoporous bioactive glasses are recently gaining importance thanks to their bone regenerative properties. Moreover, the mesoporous nature of these materials makes them suitable for drug delivery applications, opening new lines in the field of bone therapies. In this work, we have developed innovative nanodevices based on the implementation of adenosine triphosphate (ATP) and ε-poly-L-lysine molecular gates using a mesoporous bioglass as an inorganic support. The systems have been previously proved to work properly with a fluorescence probe and subsequently with an antibiotic (levofloxacin) and an antitumoral drug (doxorubicin). The bioactivity of the prepared materials has also been tested, giving promising results. Finally, in vitro cell culture studies have been carried out; demonstrating that this gated devices can provide useful approaches for bone cancer and bone infection treatments.

Biotechnology• 2021• arXiv
Access Full TextView Details
Periodicals

Novel approach for non-invasive phase-sensitive 2D imaging of biological objects with photovoltaic trapping

A novel non-invasive microscopy technique for imaging and sizing of folded DNA molecules with the use of photovoltaic tweezers and phase-sensitive detection is elaborated and realized. This novel method is compared with the state-of-the-art method of visualization of DNA molecules by fluorescent microscopy technique which requires the labeling of the DNA by dye molecules. The advantage of the novel method is no requirement for the incubation of DNA with a fluorescent label, as well as the simultaneous observation of the light-induced inside the crystal refractive lattice (i.e. photovoltaic field configuration) and the trapped micro-objects by the phase-contrast method. The suggested novel method provides the accurate measurement of the size and shape of the folded DNA molecules as well as the determination of the charged or neutral nature of the trapped bio-objects by their disposition relative to the lattice fringes. We demonstrate that the labeling of DNA causes an overestimation of the molecular size. The method can be extended to the other bio-objects. The high-performance photovoltaic tweezers operating in an autonomous regime as lab-on-a-chip devices are promising for applications in integrated optics, microscopy, micro- and nanoelectronics, and biotechnology.

Biotechnology• 2025• arXiv
Access Full TextView Details
Periodicals

Microfluidic Molecular Communication Transmitter Based on Hydrodynamic Gating

Molecular Communications (MC) is a bio-inspired paradigm for transmitting information using chemical signals, which can enable novel applications at the junction of biotechnology, nanotechnology, and information and communication technologies. However, designing efficient and reliable MC systems poses significant challenges due to the complex nature of the physical channel and the limitations of the micro/nanoscale transmitter and receiver devices. In this paper, we propose a practical microfluidic transmitter architecture for MC based on hydrodynamic gating, a widely utilized technique for generating chemical waveforms in microfluidic channels with high spatiotemporal resolution. We develop an approximate analytical model that can capture the fundamental characteristics of the generated molecular pulses, such as pulse width, pulse amplitude, and pulse delay, as functions of main system parameters, such as flow velocity and gating duration. We validate the accuracy of our model by comparing it with finite element simulations using COMSOL Multiphysics under various system settings. Our analytical model can enable the optimization of microfluidic transmitters for MC applications in terms of minimizing intersymbol interference and maximizing data transmission rate.

Biotechnology• 2023• arXiv
Access Full TextView Details
Periodicals

Nanotechnology Applications The future arrived suddenly

There is already a significant time, but it gives the sensation of extremely short,nanotechnology has become one of the most promising scientific hopes in innumerable human domains. Now the hope become reality. Countless scientific studies in several areas of knowledge have been made since the nanoscale emergence, carrying their contribution to the nanoscience development. The recent research in this field allowed the union of interests among several areas, such as physical sciences, molecular engineering, biology, biotechnology and medicine for example, contributing to the investigation of biosystems at a nanoscale. In this work begin discussing nanotechnology in a general way. Then nanotechnology and the applications in industry, in electronics and in medicine are presented and some discussion is proposed in order to define the boundaries for the advances on those areas. In the end, nanotechnology is discussed in terms of ethics and in terms of the borders that nanotechnology applications must satisfyand concluding notes are presented, highlighting the results of the analysis. Important considerations are made about the close connection between ethics and the nanotechnology and the effects over the society and values. Some future directions for the research are suggested.

Biotechnology• 2022• arXiv
Access Full TextView Details
Periodicals

Co-Generative De Novo Functional Protein Design

De novo functional protein design aims to generate protein sequences that realize specified biochemical functions without relying on evolutionary templates, enabling broad applications in biotechnology and medicine. Existing approaches adopt either direct function-to-sequence mapping or decoupled structure-sequence generation strategies but often fail to achieve functionality and foldability simultaneously. To address this, we propose CodeFP, a Co-generative protein language model for de novo Functional Protein design that simultaneously decodes sequence and structure tokens, thereby enabling superior simultaneous realization of functionality and foldability. CodeFP utilizes functional local structures to enrich functional semantic encodings, overcoming the suboptimal translation of flat encodings into structure tokens, while introducing auxiliary functional supervision to alleviate training ambiguity stemming from the one-to-many structure-to-token mapping. Extensive experiments show that CodeFP consistently achieves average improvements of 6.1% in functional consistency and 3.2% in foldability over the strongest baseline.

Biotechnology• 2026• arXiv
Access Full TextView Details
Periodicals

The variable quality of metadata about biological samples used in biomedical experiments

We present an analytical study of the quality of metadata about samples used in biomedical experiments. The metadata under analysis are stored in two well-known databases: BioSample---a repository managed by the National Center for Biotechnology Information (NCBI), and BioSamples---a repository managed by the European Bioinformatics Institute (EBI). We tested whether 11.4M sample metadata records in the two repositories are populated with values that fulfill the stated requirements for such values. Our study revealed multiple anomalies in the metadata. Most metadata field names and their values are not standardized or controlled. Even simple binary or numeric fields are often populated with inadequate values of different data types. By clustering metadata field names, we discovered there are often many distinct ways to represent the same aspect of a sample. Overall, the metadata we analyzed reveal that there is a lack of principled mechanisms to enforce and validate metadata requirements. The significant aberrancies that we found in the metadata are likely to impede search and secondary use of the associated datasets.

Biotechnology• 2018• arXiv
Access Full TextView Details
Periodicals

Simulation aspects of patterning polymer films via evaporative lithography and composite substrates

The continuing development of evaporative lithography is important for many areas such as the creation of photonic crystals for optronics and microelectronics, the development of biosensors for medical applications and biotechnology, and for the formation of functional coatings for nanotechnology, including the application of thin, protective polymer coatings. The article proposes a mathematical model that allows us to explain the basic mechanisms of the formation of thin polymer films (less than 50 $μ$m thick) during their deposition onto a composite substrate by methanol evaporation from a solution. If the thermal conductivity of the substrate is spatially non-uniform, this results in inhomogeneous evaporation along the free film surface. Therefore, as the film dries, a patterned polymer coating is left behind on the substrate. The mathematical model described here is based on the lubrication approximation and takes into account the dependence of the solution density on the concentration. The numerical computation results are in qualitative agreement with the experimental data of other authors. The article shows that solutal Marangoni flow plays a primary role in the process under consideration. This study allows us to better understand the mechanisms that can be used in evaporative lithography.

Biotechnology• 2024• arXiv
Access Full TextView Details
Periodicals

Evolving methods for rational de novo design of functional RNA molecules

Artificial RNA molecules with novel functionality have many applications in synthetic biology, pharmacy and white biotechnology. The de novo design of such devices using computational methods and prediction tools is a resource-efficient alternative to experimental screening and selection pipelines. In this review, we describe methods common to many such computational approaches, thoroughly dissect these methods and highlight open questions for the individual steps. Initially, it is essential to investigate the biological target system, the regulatory mechanism that will be exploited, as well as the desired components in order to define design objectives. Subsequent computational design is needed to combine the selected components and to obtain novel functionality. This process can usually be split into constrained sequence sampling, the formulation of an optimization problem and an in silico analysis to narrow down the number of candidates with respect to secondary goals. Finally, experimental analysis is important to check whether the defined design objectives are indeed met in the target environment and detailed characterization experiments should be performed to improve the mechanistic models and detect missing design requirements.

Biotechnology• 2019• arXiv
Access Full TextView Details
Periodicals

Engineering quantum optical responses of microtubules through tryptophan-network simulations and ultraviolet spectroscopy

Microtubules host dense ultraviolet-absorbing aromatic networks, suggesting an opportunity to engineer their optical response for biotechnology. Here we assess the feasibility of tuning microtubule fluorescence by combining an excitonic radiative-coupling model with molecular-dynamics-derived microtubule-like assemblies and steady-state absorbance and fluorescence measurements in microplate geometries. Simulations quantify how positional and orientational fluctuations reshape radiative rates and quantum yield, and predict how perturbing the tryptophan network by removing a specific site, adding an extra tryptophan at candidate binding pockets, or using mixed modification fractions can modulate emission. Experiments on porcine tubulin dimers and taxol-stabilized microtubules support these trends: polymerization enhances microtubule quantum yield at 280 nm and yields bounded changes at 295 nm due to scattering, while added L-tryptophan reproducibly quenches microtubules at both wavelengths. Together, theory and experiment provide evidence for chemically addressable tuning of microtubule quantum yield and motivate design rules for engineered microtubule photonics.

Biotechnology• 2026• arXiv
Access Full TextView Details
Periodicals

Quantitative modelling of nutrient-limited growth of bacterial colonies in microfluidic cultivation

Nutrient gradients and limitations play a pivotal role in the life of all microbes, both in their natural habitat as well as in artificial, microfluidic systems. Spatial concentration gradients of nutrients in densely packed cell configurations may locally affect the bacterial growth leading to heterogeneous micropopulations. A detailed understanding and quantitative modelling of cellular behaviour under nutrient limitations is thus highly desirable. We use microfluidic cultivations to investigate growth and microbial behaviour of the model organism Corynebacterium glutamicum under well-controlled conditions. With a reaction-diffusion type model, parameters are extracted from steady-state experiments with a one-dimensional nutrient gradient. Subsequentially, we employ particle-based simulations with these parameters to predict the dynamical growth of a colony in two dimensions. Comparing the results of those simulations with microfluidic experiments yields excellent agreement. Our modelling approach lays the foundation for a better understanding of dynamic microbial growth processes, both in nature and in applied biotechnology.

Biotechnology• 2018• arXiv
Access Full TextView Details
Periodicals

Density shock waves in confined microswimmers

Motile and driven particles confined in microfluidic channels exhibit interesting emergent behavior from propagating density bands to density shock waves. A deeper understanding of the physical mechanisms responsible for these emergent structures is relevant to a number of physical and biomedical applications. Here, we study the formation of density shock waves in the context of an idealized model of microswimmers confined in a narrow channel and subject to a uniform external flow. Interestingly, these density shock waves exhibit a transition from `subsonic' with compression at the back to `supersonic' with compression at the front of the population as the intensity of the external flow increases. This behavior is the result of a non-trivial interplay between hydrodynamic interactions and geometric confinement, and is confirmed by a novel quasilinear wave model that properly captures the dependence of the shock formation on the external flow. These findings can be used to guide the development of novel mechanisms for controlling the emergent density distribution and average population speed, with potentially profound implications on various processes in industry and biotechnology such as the transport and sorting of cells in flow channels.

Biotechnology• 2015• arXiv
Access Full TextView Details
Periodicals

Three-Dimensional FDTD Simulation of Biomaterial Exposure to Electromagnetic Nanopulses

Ultra-wideband (UWB) electromagnetic pulses of nanosecond duration, or nanopulses, have been recently approved by the Federal Communications Commission for a number of various applications. They are also being explored for applications in biotechnology and medicine. The simulation of the propagation of a nanopulse through biological matter, previously performed using a two-dimensional finite difference-time domain method (FDTD), has been extended here into a full three-dimensional computation. To account for the UWB frequency range, a geometrical resolution of the exposed sample was $0.25 mm$, and the dielectric properties of biological matter were accurately described in terms of the Debye model. The results obtained from three-dimensional computation support the previously obtained results: the electromagnetic field inside a biological tissue depends on the incident pulse rise time and width, with increased importance of the rise time as the conductivity increases; no thermal effects are possible for the low pulse repetition rates, supported by recent experiments. New results show that the dielectric sample exposed to nanopulses behaves as a dielectric resonator. For a sample in a cuvette, we obtained the dominant resonant frequency and the $Q$-factor of the resonator.

Biotechnology• 2005• arXiv
Access Full TextView Details
Periodicals

Achieving DNA Labeling Capacity with Minimum Labels through Extremal de Bruijn Subgraphs

DNA labeling is a tool in molecular biology and biotechnology to visualize, detect, and study DNA at the molecular level. In this process, a DNA molecule is labeled by a set of specific patterns, referred to as labels, and is then imaged. The resulting image is modeled as an $(\ell+1)$-ary sequence, where $\ell$ is the number of labels, in which any non-zero symbol indicates the appearance of the corresponding label in the DNA molecule. The labeling capacity refers to the maximum information rate that can be achieved by the labeling process for any given set of labels. The main goal of this paper is to study the minimum number of labels of the same length required to achieve the maximum labeling capacity of 2 for DNA sequences or $\log_2q$ for an arbitrary alphabet of size $q$. The solution to this problem requires the study of path unique subgraphs of the de Bruijn graph with the largest number of edges. We provide upper and lower bounds on this value. We draw new connections to existing literature that let us prove an asymptotic result as the label length tends to infinity.

Biotechnology• 2024• arXiv
Access Full TextView Details
Periodicals

Molecular Diffusion Replaces Capillary Pumping in Phase-Change Driven Nanopumps

Nano-scale fluid transport has vast applications spanning from water desalination to biotechnology [1,2]. It is possible to pump fluids in nano-conduits using pressure gradients [3], thermal methods [4], electric [5,6] and magnetic fields [7], and with manipulations of surface chemistry and electric fields [8-10]. Inspired by the capillary-driven phase change heat transfer devices, we present a phase-change driven nanopump operating almost isothermally. Meticulous computational experiments on different sized nanopumps revealed efficient operation of the pump despite the reduction in system size that extinguishes capillary pumping by annihilating the liquid meniscus structures. Measuring the density distribution of liquid in cross sections near to the evaporating and condensing liquid-vapor interfaces, we discovered that phase change induced molecular scale mass diffusion mechanism replaces the capillary pumping in the absence of meniscus structures. Therefore, proposed pumps can serve as a part of both nanoelectromechanical (NEMS) and microelectromechanical systems (MEMS) with similar working efficiencies, and can be used for continuous gas separation applications.

Biotechnology• 2018• arXiv
Access Full TextView Details
Periodicals

Microfluidic bioanalytical flow cells for biofilm studies: A review

Bacterial biofilms are among the oldest and most prevalent multicellular life forms on Earth and are increasingly relevant in research areas related to industrial fouling, medicine and biotechnology. The main hurdles to obtaining definitive experimental results include time-varying biofilm properties, structural and chemical heterogeneity, and especially their strong sensitivity to environmental cues. Therefore, in addition to judicious choice of measurement tools, a well-designed biofilm study requires strict control over experimental conditions, more so than most chemical studies. Due to excellent control over a host of physiochemical parameters, microfluidic flow cells have become indispensable in microbiological studies. Not surprisingly, the number of lab-on-chip studies focusing on biofilms and other microbiological systems with expanded analytical capabilities has expanded rapidly in the past decade. In this paper, we comprehensively review the current state of microfluidic bioanalytical research applied to bacterial biofilms and offer a perspective on new approaches that are expected to drive continued advances in this field.

Biotechnology• 2021• arXiv
Access Full TextView Details
Periodicals

Large area monocrystalline and surfactant-free copper microflake synthesis

Copper is one of the most extensively studied materials for energy conversion and catalytic systems, with a wide range of other applications from nanophotonics to biotechnology. However, existing synthesis methods are limited with many undesirable by-products and poorly defined morphologies. Here, we report a surfactant-free on-substrate wet synthesis approach that yields monocrystalline metallic Cu microflakes with (111) crystalline exposed surface. By systematically studying the growth mechanism, we achieve unprecedented sizes of more than 130 μm, which is two orders of magnitude larger than reported in most previous studies, along with higher aspect ratios of over 400. Furthermore, we show distinctly higher stability against oxidation provided by the halide adlayer. Overall, our facile synthesis approach delivers an exciting venue for the emerging fields of catalysis and nanophotonics.

Biotechnology• 2025• arXiv
Access Full TextView Details
Previous1...1314151617...79Next