MOTIVATION: The complex dynamics of cancer evolution, driven by mutation and selection, underlies the molecular heterogeneity observed in tumors. The evolutionary histories of tumors of different patients can be encoded as mutation trees and reconstructed in high resolution from single-cell sequencing data, offering crucial insights for studying fitness effects of and epistasis among mutations. Existing models, however, either fail to separate mutation and selection or neglect the evolutionary histories encoded by the tumor phylogenetic trees. RESULTS: We introduce FiTree, a tree-structured multi-type branching process model with epistatic fitness parameterization and a Bayesian inference scheme to learn fitness landscapes from single-cell tumor mutation trees. Through simulations, we demonstrate that FiTree outperforms state-of-the-art methods in inferring the fitness landscape underlying tumor evolution. Applying FiTree to a single-cell acute myeloid leukemia dataset, we identify epistatic fitness effects consistent with known biological findings and quantify uncertainty in predicting future mutational events. The new model unifies probabilistic graphical models of cancer progression with population genetics, offering a principled framework for understanding tumor evolution and informing therapeutic strategies. AVAILABILITY AND IMPLEMENTATION: The Python package FiTree and the analysis workflows are available at https://github.com/cbg-ethz/FiTree.

This paper presents a system integration approach for a 6-DoF (Degree of Freedom) collaborative robot to operate a pipette for liquid dispensing. Its technical development is three-fold. First, we designed an end-effector for holding and triggering manual pipettes. Second, we took advantage of direct teaching to specify global labware poses and planned robotic motion based on them. Third, we leveraged hand-mounted cameras and visual classifiers to predict and correct positioning errors, which allowed precisely attaching pipettes and tips without calibration. Through experiments and analysis, we confirmed that the developed system, especially the planning and visual recognition methods, could help secure high-precision and flexible liquid dispensing. The developed system is suitable for low-frequency, high-repetition biochemical liquid dispensing tasks. We expect it to promote the deployment of collaborative robots for laboratory automation and thus improve the experimental efficiency without significantly customizing a laboratory environment.Note to Practitioners—The proposed system helps to automate low-frequency, high-repetition biochemical experiments using a vertical articulated robot with uncalibrated hand-mounted cameras and TCP (Tool Center Point). It can be quickly deployed in tight lab spaces or beside existing automation instruments for experiments. Implementing the system does not require high-quality cameras or precise manufacturing. The system relies on software, particularly vision compensation, and the flexibility provided by unfixed racks to successfully perform pipetting tasks. We particularly recommend using collaborative robots to implement the proposed system. Collaborative robots typically meet safety requirements and do not need to be enclosed in a cage. This allows them to be deployed in the same workspace as human researchers, enabling efficient lab experiments. Human researchers can prepare tips and microwell plates and place them in front of the robot with a certain degree of freedom, which is less burdensome than traditional automatic devices that require precise placement of tips and plates in specified positions. Practitioners can view an example of the robot working with a plant phenotyping system for screening chemicals in the supplementary video.

This paper proposes a novel metric learning method for fair face attribute recognition. Datasets with imbalanced sample distributions can spoil the fair discrimination ability of deep learning models. This problem becomes more complex in multi-label classification tasks due to the variety of imbalance levels for each label. To tackle this problem, we propose Imbalance-Aware Adaptive Margin (IAAM). IAAM utilizes prior information on data imbalance with new parameters that control the relative margins between classes for each label. Specifically, it adaptively tunes margins in the metric learning loss to give larger margins for minority classes and smaller margins for majority classes. The proposed method is a flexible reformulation of previous studies for multi-label classification tasks. We performed experiments on the Celeb-A and LFWA datasets and evaluated with fair classification metrics. Our findings showed that the IAAM led to excellent performance on fair face attribute recognition both in the weakly imbalanced labels and strongly imbalanced labels.

This paper proposes an efficient iris localization method without using iris segmentation and circle fitting. Conventional iris localization methods first extract iris regions by using semantic segmentation methods such as U-Net. Afterward, the inner and outer iris circles are localized using the traditional circle fitting algorithm. However, this approach requires high-resolution encoder-decoder networks for iris segmentation, so it causes computational costs to be high. In addition, traditional circle fitting tends to be sensitive to noise in input images and fitting parameters, causing the iris recognition performance to be poor. To solve these problems, we propose an iris localization network (ILN), that can directly localize pupil and iris circles with eyelid points from a low-resolution iris image. We also introduce a pupil refinement network (PRN) to improve the accuracy of pupil localization. Experimental results show that the combination of ILN and PRN works in 34.5 ms for one iris image on a CPU, and its localization performance out-performs conventional iris segmentation methods. In addition, generalized evaluation results show that the proposed method has higher robustness for datasets in different domain than other segmentation methods. Furthermore, we also confirm that the proposed ILN and PRN improve the iris recognition accuracy.

Tumour progression is an evolutionary process in which different clones evolve over time, leading to intra-tumour heterogeneity. Interactions between clones can affect tumour evolution and hence disease progression and treatment outcome. Intra-tumoural pairs of mutations that are overrepresented in a co-occurring or clonally exclusive fashion over a cohort of patient samples may be suggestive of a synergistic effect between the different clones carrying these mutations. We therefore developed a novel statistical testing framework, called GeneAccord, to identify such gene pairs that are altered in distinct subclones of the same tumour. We analysed our framework for calibration and power. By comparing its performance to baseline methods, we demonstrate that to control type I errors, it is essential to account for the evolutionary dependencies among clones. In applying GeneAccord to the single-cell sequencing of a cohort of 123 acute myeloid leukaemia patients, we find 1 clonally co-occurring and 8 clonally exclusive gene pairs. The clonally exclusive pairs mostly involve genes of the key signalling pathways.

BACKGROUND: Studies using quantitative experimental methods have shown that intracellular spatial distribution of molecules plays a central role in many cellular systems. Spatially resolved computer simulations can integrate quantitative data from these experiments to construct physically accurate models of the systems. Although computationally expensive, microscopic resolution reaction-diffusion simulators, such as Spatiocyte can directly capture intracellular effects comprising diffusion-limited reactions and volume exclusion from crowded molecules by explicitly representing individual diffusing molecules in space. To alleviate the steep computational cost typically associated with the simulation of large or crowded intracellular compartments, we present a parallelized Spatiocyte method called pSpatiocyte. RESULTS: The new high-performance method employs unique parallelization schemes on hexagonal close-packed (HCP) lattice to efficiently exploit the resources of common workstations and large distributed memory parallel computers. We introduce a coordinate system for fast accesses to HCP lattice voxels, a parallelized event scheduler, a parallelized Gillespie's direct-method for unimolecular reactions, and a parallelized event for diffusion and bimolecular reaction processes. We verified the correctness of pSpatiocyte reaction and diffusion processes by comparison to theory. To evaluate the performance of pSpatiocyte, we performed a series of parallelized diffusion runs on the RIKEN K computer. In the case of fine lattice discretization with low voxel occupancy, pSpatiocyte exhibited 74% parallel efficiency and achieved a speedup of 7686 times with 663552 cores compared to the runtime with 64 cores. In the weak scaling performance, pSpatiocyte obtained efficiencies of at least 60% with up to 663552 cores. When executing the Michaelis-Menten benchmark model on an eight-core workstation, pSpatiocyte required 45- and 55-fold shorter runtimes than Smoldyn and the parallel version of ReaDDy, respectively. As a high-performance application example, we study the dual phosphorylation-dephosphorylation cycle of the MAPK system, a typical reaction network motif in cell signaling pathways. CONCLUSIONS: pSpatiocyte demonstrates good accuracies, fast runtimes and a significant performance advantage over well-known microscopic particle methods in large-scale simulations of intracellular reaction-diffusion systems. The source code of pSpatiocyte is available at https://spatiocyte.org.

This paper describes an approach of the transporting and suppressing control of a rotating cargo for a jib crane. First, we show that the angle of the twisting cargo is measured using inertial measurement unit, and next proposed the gyro system with a control moment gyro implemented on the cargo. In experiments, we confirmed to transport the cargo with preventing the translational and twist sway using the gyro system.

Cellular heterogeneity, which plays an essential role in biological phenomena, such as drug resistance and migration, is considered to arise from intrinsic (i.e., reaction kinetics) and extrinsic (i.e., protein variability) noise in the cell. However, the mechanistic effects of these types of noise to determine the heterogeneity of signal responses have not been elucidated. Here, we report that the output of epidermal growth factor (EGF) signaling activity is modulated by cellular noise, particularly by extrinsic noise of particular signaling components in the pathway. We developed a mathematical model of the EGF signaling pathway incorporating regulation between extracellular signal-regulated kinase (ERK) and nuclear pore complex (NPC), which is necessary for switch-like activation of the nuclear ERK response. As the threshold of switch-like behavior is more sensitive to perturbations than the graded response, the effect of biological noise is potentially critical for cell fate decision. Our simulation analysis indicated that extrinsic noise, but not intrinsic noise, contributes to cell-to-cell heterogeneity of nuclear ERK. In addition, we accurately estimated variations in abundance of the signal proteins between individual cells by direct comparison of experimental data with simulation results using Apparent Measurement Error (AME). AME was constant regardless of whether the protein levels varied in a correlated manner, while covariation among proteins influenced cell-to-cell heterogeneity of nuclear ERK, suppressing the variation. Simulations using the estimated protein abundances showed that each protein species has different effects on cell-to-cell variation in the nuclear ERK response. In particular, variability of EGF receptor, Ras, Raf, and MEK strongly influenced cellular heterogeneity, while others did not. Overall, our results indicated that cellular heterogeneity in response to EGF is strongly driven by extrinsic noise, and that such heterogeneity results from variability of particular protein species that function as sensitive nodes, which may contribute to the pathogenesis of human diseases.

Oxidative stress mediated clustering of membrane protein band 3 plays an essential role in the clearance of damaged and aged red blood cells (RBCs) from the circulation. While a number of previous experimental studies have observed changes in band 3 distribution after oxidative treatment, the details of how these clusters are formed and how their properties change under different conditions have remained poorly understood. To address these issues, a framework that enables the simultaneous monitoring of the temporal and spatial changes following oxidation is needed. In this study, we established a novel simulation strategy that incorporates deterministic and stochastic reactions with particle reaction-diffusion processes, to model band 3 cluster formation at single molecule resolution. By integrating a kinetic model of RBC antioxidant metabolism with a model of band 3 diffusion, we developed a model that reproduces the time-dependent changes of glutathione and clustered band 3 levels, as well as band 3 distribution during oxidative treatment, observed in prior studies. We predicted that cluster formation is largely dependent on fast reverse reaction rates, strong affinity between clustering molecules, and irreversible hemichrome binding. We further predicted that under repeated oxidative perturbations, clusters tended to progressively grow and shift towards an irreversible state. Application of our model to simulate oxidation in RBCs with cytoskeletal deficiency also suggested that oxidation leads to more enhanced clustering compared to healthy RBCs. Taken together, our model enables the prediction of band 3 spatio-temporal profiles under various situations, thus providing valuable insights to potentially aid understanding mechanisms for removing senescent and premature RBCs.

Distributed systems are complex, being usually composed of several subsystems running in parallel. Concurrent execution and inter-process communication in these systems are prone to errors that are difficult to detect by traditional testing, which does not cover every possible program execution. Unlike testing, model checking can detect such faults in a concurrent system by exploring every possible state of the system. However, most model-checking techniques require that a system be described in a modeling language. Although this simplifies verification, faults may be introduced in the implementation. Recently, some model checkers verify program code at runtime but tend to be limited to stand-alone programs. This paper proposes cache-based model checking, which relaxes this limitation to some extent by verifying one process at a time and running other processes in another execution environment. This approach has been implemented as an extension of Java PathFinder, a Java model checker. It is a scalable and promising technique to handle distributed systems. To support a larger class of distributed systems, a checkpointing tool is also integrated into the verification system. Experimental results on various distributed systems show the capability and scalability of cache-based model checking.

In this paper, we propose a new head pose tracking method for mobile devices. Recently, head pose tracking technologies are expected to be incorporated into various situations such as robot vision. Especially, we focus on the applications using a mobile system. However, head pose estimation methods usually require a high performance hardware although the mobile systems have limited computational resource. Therefore, we propose a low cost computing algorithm of head pose tracking for the purpose of developing mobile system applications. The proposed method has two stages: (1) fast rough tracking and (2) iterative sampling stage. The proposed method has a merit of low computing cost, and is able to be applied to mobile systems. In order to confirm the effectiveness of the proposed method, we show the comparison results of two types of iterative sampling algorithms. The experimental results demonstrate that our method can be incorporated into actual mobile system applications.

In this paper, we propose a practical method for eye blink detection using a monocular system. Eye blink detection is an important technology in many situations such as facial action analysis and signal processing. However, automatic eye blink detection is quite difficult since the eye blink is occurred fast. Fast head tracking and eye detection methods are therefore required in real environment. The proposed method is based on the facial feature point tracking algorithm by using particle filtering. The proposed method works at over 60fps and is able to detect accurate blink motion in real time although our system require only one USB camera. In order to confirm the effectiveness, we show some of applications using our blink detection system.

Correctness of workflows is one of the most important properties for quality improvement of workflows. It is a consistency property of workflows on the control flow perspective. In this paper, we extend correctness property of acyclic workflows to that of acyclic workflows with multiple starts and/or ends. The extended correctness is a natural extension of the original correctness property. It is preserved in "vertical'' composition of workflows and "vertical'' division of them. Moreover, we explain how to apply the extend correctness and its properties above to incremental verification of very large workflows on the control flow perspective.

In this paper, we introduce an algorithm called "EVA" (Evidence Verification Algorithm), which verifies consistency of life cycles of evidence-documents in workflows. As syntax of workflows, we use extended UML activity diagrams, which have additional information about evidence-documents. EVA verifies the existence of consistent sequences of flows between occurrences of evidence-documents in a workflow. It is significant to verify consistency of life cycles of evidence-documents, since one can find some defects of a workflow itself by checking inconsistent life cycles of evidence-documents in the workflow.

MOTIVATION: Molecular biotechnology now makes it possible to build elaborate systems models, but the systems biology community needs information standards if models are to be shared, evaluated and developed cooperatively. RESULTS: We summarize the Systems Biology Markup Language (SBML) Level 1, a free, open, XML-based format for representing biochemical reaction networks. SBML is a software-independent language for describing models common to research in many areas of computational biology, including cell signaling pathways, metabolic pathways, gene regulation, and others. AVAILABILITY: The specification of SBML Level 1 is freely available from http://www.sbml.org/

Abstract Summary: A new version of the E-Cell simulation system, which runs on Windows as well as Linux, has been released as free software under the terms of the GNU General Public License. Availability: Downloadable from http://www.E-Cell.org

Article Free Access Share on The E-CELL project: towards integrative simulation of cellular processes Authors: Masaru Tomita Laboratory for Bioinformatics and Department of Environmental Informatics Laboratory for Bioinformatics and Department of Environmental InformaticsView Profile , Kenta Hashimoto Laboratory for Bioinformatics and School of Media and Governance Laboratory for Bioinformatics and School of Media and GovernanceView Profile , Koichi Takahashi Laboratory for Bioinformatics and School of Media and Governance Laboratory for Bioinformatics and School of Media and GovernanceView Profile , Yuri Matsuzaki Laboratory for Bioinformatics and School of Media and Governance Laboratory for Bioinformatics and School of Media and GovernanceView Profile , Ryo Matsushima Laboratory for Bioinformatics and School of Media and Governance Laboratory for Bioinformatics and School of Media and GovernanceView Profile , Katsuyuki Yugi Laboratory for Bioinformatics and School of Media and Governance Laboratory for Bioinformatics and School of Media and GovernanceView Profile , Fumihiko Miyoshi Laboratory for Bioinformatics and School of Media and Governance Laboratory for Bioinformatics and School of Media and GovernanceView Profile , Hisako Nakano Laboratory for Bioinformatics and Department of Policy Management, Keio University, 5322 Endo, Fujisawa, 252-8520 Japan Laboratory for Bioinformatics and Department of Policy Management, Keio University, 5322 Endo, Fujisawa, 252-8520 JapanView Profile , Yusuke Saito Laboratory for Bioinformatics and Department of Environmental Informatics Laboratory for Bioinformatics and Department of Environmental InformaticsView Profile , S. Shimizu Laboratory for Bioinformatics and Department of Zoology, Cambridge University, CB2 3EJ, UK Laboratory for Bioinformatics and Department of Zoology, Cambridge University, CB2 3EJ, UKView Profile , Yoichi Nakayama Laboratory for Bioinformatics and Department of Environmental Informatics Laboratory for Bioinformatics and Department of Environmental InformaticsView Profile Authors Info & Claims RECOMB '00: Proceedings of the fourth annual international conference on Computational molecular biologyApril 2000 Pages 290–298https://doi.org/10.1145/332306.332567Published:08 April 2000Publication History 1citation569DownloadsMetricsTotal Citations1Total Downloads569Last 12 Months13Last 6 weeks5 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

MOTIVATION: Genome sequencing projects and further systematic functional analyses of complete gene sets are producing an unprecedented mass of molecular information for a wide range of model organisms. This provides us with a detailed account of the cell with which we may begin to build models for simulating intracellular molecular processes to predict the dynamic behavior of living cells. Previous work in biochemical and genetic simulation has isolated well-characterized pathways for detailed analysis, but methods for building integrative models of the cell that incorporate gene regulation, metabolism and signaling have not been established. We, therefore, were motivated to develop a software environment for building such integrative models based on gene sets, and running simulations to conduct experiments in silico. RESULTS: E-CELL, a modeling and simulation environment for biochemical and genetic processes, has been developed. The E-CELL system allows a user to define functions of proteins, protein-protein interactions, protein-DNA interactions, regulation of gene expression and other features of cellular metabolism, as a set of reaction rules. E-CELL simulates cell behavior by numerically integrating the differential equations described implicitly in these reaction rules. The user can observe, through a computer display, dynamic changes in concentrations of proteins, protein complexes and other chemical compounds in the cell. Using this software, we constructed a model of a hypothetical cell with only 127 genes sufficient for transcription, translation, energy production and phospholipid synthesis. Most of the genes are taken from Mycoplasma genitalium, the organism having the smallest known chromosome, whose complete 580 kb genome sequence was determined at TIGR in 1995. We discuss future applications of the E-CELL system with special respect to genome engineering. AVAILABILITY: The E-CELL software is available upon request. SUPPLEMENTARY INFORMATION: The complete list of rules of the developed cell model with kinetic parameters can be obtained via our web site at: http://e-cell.org/.

Abstract. We introduce an Emacs interface for writing HOL proof scripts in SML based on the Computing-as-Editing paradigm. Tactics in a proof script are considered as constraints, and the process of interactive theorem proving becomes that of solving constraints. In addition, constraint solving is subsumed by the process of editing a proof script. Tactics are executed while the script is being edited. The user does not have to pay attention to the status of the HOL prover. In our interface, the user can also enjoy proof-by-pointing. The result of proof-by-pointing is inserted as a tactic into a proof script. We expect that our interface will be widely used as an extension of the familiar HOL mode on Emacs.

In this paper we propose a method to implement the moving patterns which are consecutively related in a small computer system. Suppose that the patterns are constructed of many block elements. A pattern is derived by the operation ( such as AND, OR, EXOR, MOVE, ZOOM, ROTATE,. .. ), with another pattern if it is required as operand. The parallel execution on a multiple microprocessor system is also discussed.