A5060265779- Cell Image Analysis Techniques
- AI in cancer detection
- Light effects on plants
- Photoreceptor and optogenetics research
- Photosynthetic Processes and Mechanisms
- Fault Detection and Control Systems
- Advanced Control Systems Optimization
- Gene Regulatory Network Analysis
- CRISPR and Genetic Engineering
- Digital Imaging for Blood Diseases
- Control Systems and Identification
- Hydrological Forecasting Using AI
- Genetics, Bioinformatics, and Biomedical Research
- DNA Repair Mechanisms
- Fungal and yeast genetics research
- Bacterial Genetics and Biotechnology
- Advanced Fluorescence Microscopy Techniques
- Carcinogens and Genotoxicity Assessment
- Mechanical and Optical Resonators
- Gene expression and cancer classification
- Bacterial Identification and Susceptibility Testing
- Image Processing Techniques and Applications
- Advanced Neural Network Applications
- Simulation Techniques and Applications
- Photochromic and Fluorescence Chemistry
École Polytechnique Fédérale de Lausanne
2019-2024
University of Belgrade
2018
The identification of cell borders ('segmentation') in microscopy images constitutes a bottleneck for large-scale experiments. For the model organism Saccharomyces cerevisiae, current segmentation methods face challenges when cells bud, crowd, or exhibit irregular features. We present convolutional neural network (CNN) named YeaZ, underlying training set high-quality segmented yeast (>10 000 cells) including mutants, stressed cells, and time courses, as well graphical user interface web...
Abstract The ability to independently control the expression of different genes is important for quantitative biology. Using budding yeast, we characterize GAL1pr , GALL MET3pr CUP1pr PHO5pr tetOpr terminator - Z 3 EV, blue-light inducible optogenetic systems El222 -LIP -GLIP and red-light PhyB-PIF3. We report kinetic parameters, noise scaling, impact on growth, fundamental leakiness each system using an intuitive unit, maxGAL1. uncover disadvantages widely used tools, e.g., nonmonotonic...
Abstract Directed evolution is a powerful method in biological engineering. Current approaches draw on time-invariant selection mechanisms, ideal for evolving steady-state properties such as enzymatic activity or fluorescence intensity. A fundamental problem remains how to continuously evolve dynamic, multi-state, computational functionalities, e.g., on-off kinetics, state-specific activity, stimulus-responsiveness, switching and logic capabilities. These require pressure all of the states...
We present a novel optical nanomotion-based rapid antibiotic and antifungal susceptibility test. The technique consisted of studying the effects antibiotics or antifungals on nanometric scale displacements bacteria yeasts to assess their sensitivity resistance drugs. relies traditional microscope, video camera, custom-made image analysis software. It provides reliable results in time frame 2–4 h can be applied motile, non-motile, fast, slowly growing microorganisms. Due its extreme...
Abstract The processing of microscopy images constitutes a bottleneck for large-scale experiments. A critical step is the establishment cell borders (‘segmentation’), which required range applications such as growth or fluorescent reporter measurements. For model organism budding yeast ( Saccharomyces cerevisiae ), number methods segmentation exist. However, in experiments involving multiple cycles, stress, various mutants, cells crowd exhibit irregular visible features, necessitate frequent...
Abstract Scar-less genome editing in budding yeast with elimination of the selection marker has many advantages. Some markers such as URA3 and TRP1 can be recycled through counterselection. This permits seamless modification pop-in/pop-out (PIPO), which a DNA construct first integrates and, subsequently, homologous regions recombine excise undesired sequences. Popular approaches for creating constructs use oligonucleotides polymerase chain reaction (PCR). However, practical disadvantages....
Abstract The ease of genome editing has contributed to the popularity budding yeast as a model organism. However, palette selectable markers is in principle limited most can only be used once. Some such URA3 and TRP1 recycled through counterselection. This permits seamless modification with pop-in/pop-out (PIPO), which DNA construct first integrates and, subsequently, homologous regions recombine excise undesired sequences. Popular approaches for creating constructs use oligonucleotides...
An approach to design feedback controllers for discrete-time, uncertain, linear time-varying systems subject constraints is proposed. Building on previous contributions in the framework of time-invariant systems, each sampling period a two-step procedure carried out. In first step, set models that are consistent with past input-output data and prior assumptions built refined. This guaranteed contain also true system dynamics if considered working valid. The nature plant captured by assuming...
This manuscript contains technical details of recent results developed by the authors on adaptive model predictive control for constrained linear, time varying systems.
Abstract For quantitative systems biology, simultaneous readout of multiple cellular processes as well precise, independent control over different genes’ activities are essential. In contrast to such fluorescent proteins, inducible transcription-factor-promoter have only been characterized in an ad hoc fashion, impeding precise system-level manipulations biological and reliable modeling. We designed performed systematic benchmarks involving easy-to-communicate units characterize compare...
Abstract Why biological quality-control systems fail is often mysterious. Specifically, checkpoints such as the DNA damage checkpoint or spindle assembly are overriden after prolonged arrests allowing cells to continue dividing despite continued presence of errors. 1–4 Although critical for systems, override poorly understood quantitatively by experiment theory. Override may represent a trade-off between risk and speed, fundamental principle explaining phenomena. 5,6 Here, we derive first,...