MIMO: an efficient tool for molecular interaction maps overlap.
Ontology highlight
ABSTRACT: Background
Molecular pathways represent an ensemble of interactions occurring among molecules within the cell and between cells. The identification of similarities between molecular pathways across organisms and functions has a critical role in understanding complex biological processes. For the inference of such novel information, the comparison of molecular pathways requires to account for imperfect matches (flexibility) and to efficiently handle complex network topologies. To date, these characteristics are only partially available in tools designed to compare molecular interaction maps.Results
Our approach MIMO (Molecular Interaction Maps Overlap) addresses the first problem by allowing the introduction of gaps and mismatches between query and template pathways and permits -when necessary- supervised queries incorporating a priori biological information. It then addresses the second issue by relying directly on the rich graph topology described in the Systems Biology Markup Language (SBML) standard, and uses multidigraphs to efficiently handle multiple queries on biological graph databases. The algorithm has been here successfully used to highlight the contact point between various human pathways in the Reactome database.Conclusions
MIMO offers a flexible and efficient graph-matching tool for comparing complex biological pathways.
SUBMITTER: Di Lena P
PROVIDER: S-EPMC3680968 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:The analysis of contacts is a powerful tool to understand biomolecular function in a series of contexts, from the investigation of dynamical behavior at equilibrium to the study of nonequilibrium dynamics in which the system moves between multiple states. We thus propose a tool called CONtact ANalysis (CONAN) that, from molecular dynamics (MD) trajectories, analyzes interresidue contacts, creates videos of time-resolved contact maps, and performs correlation, principal component, and cluster analysis, revealing how specific contacts relate to functionally relevant states sampled by MD. We present how CONAN can identify features describing the dynamics of ubiquitin both at equilibrium and during mechanical unfolding. Additionally, we show the analysis of MD trajectories of an ?-synuclein mutant peptide that undergoes an ?-? conformational transition that can be easily monitored using CONAN, which identifies the multiple states that the peptide explores along its conformational dynamics. The high versatility and ease of use of the software make CONAN a tool that can significantly facilitate the understanding of the complex dynamical behavior of proteins or other biomolecules. CONAN and its documentation are freely available for download on GitHub.
| S-EPMC5883949 | biostudies-literature
Project description:Demand for high-speed wireless broadband internet service is ever increasing. Multiple-input-multiple-output (MIMO) Wireless LAN (WLAN) is becoming a promising solution for such high-speed internet service requirements. This paper proposes a novel algorithm to efficiently model the address generation circuitry of the MIMO WLAN interleaver. The interleaver used in the MIMO WLAN transceiver has three permutation steps involving floor function whose hardware implementation is the most challenging task due to the absence of corresponding digital hardware. In this work, we propose an algorithm with a mathematical background for the address generator, eliminating the need for floor function. The algorithm is converted into digital hardware for implementation on the reconfigurable FPGA platform. Hardware structure for the complete interleaver, including the read address generator and memory module, is designed and modeled in VHDL using Xilinx Integrated Software Environment (ISE) utilizing embedded memory and DSP blocks of Spartan 6 FPGA. The functionality of the proposed algorithm is verified through exhaustive software simulation using ModelSim software. Hardware testing is carried out on Zynq 7000 FPGA using Virtual Input Output (VIO) and Integrated Logic Analyzer (ILA) core. Comparisons with few recent similar works, including the conventional Look-Up Table (LUT) based technique, show the superiority of our proposed design in terms of maximum improvement in operating frequency by 196.83%, maximum reduction in power consumption by 74.27%, and reduction of memory occupancy by 88.9%. In the case of throughput, our design can deliver 8.35 times higher compared to IEEE 802.11n requirement.
| S-EPMC8205304 | biostudies-literature
Project description:Tumor-specific elucidation of physical and functional oncoprotein interactions could improve tumorigenic mechanism characterization and therapeutic response prediction. Current interaction models and pathways, however, lack context specificity and are not oncoprotein specific. We introduce SigMaps as context-specific networks, comprising modulators, effectors and cognate binding-partners of a specific oncoprotein. SigMaps are reconstructed de novo by integrating diverse evidence sources-including protein structure, gene expression and mutational profiles-via the OncoSig machine learning framework. We first generated a KRAS-specific SigMap for lung adenocarcinoma, which recapitulated published KRAS biology, identified novel synthetic lethal proteins that were experimentally validated in three-dimensional spheroid models and established uncharacterized crosstalk with RAB/RHO. To show that OncoSig is generalizable, we first inferred SigMaps for the ten most mutated human oncoproteins and then for the full repertoire of 715 proteins in the COSMIC Cancer Gene Census. Taken together, these SigMaps show that the cell's regulatory and signaling architecture is highly tissue specific.
| S-EPMC7878435 | biostudies-literature
Project description:MOTIVATION:Molecular interaction maps have emerged as a meaningful way of representing biological mechanisms in a comprehensive and systematic manner. However, their static nature provides limited insights to the emerging behaviour of the described biological system under different conditions. Computational modelling provides the means to study dynamic properties through in silico simulations and perturbations. We aim to bridge the gap between static and dynamic representations of biological systems with CaSQ, a software tool that infers Boolean rules based on the topology and semantics of molecular interaction maps built with CellDesigner. RESULTS:We developed CaSQ by defining conversion rules and logical formulas for inferred Boolean models according to the topology and the annotations of the starting molecular interaction maps. We used CaSQ to produce executable files of existing molecular maps that differ in size, complexity and the use of Systems Biology Graphical Notation (SBGN) standards. We also compared, where possible, the manually built logical models corresponding to a molecular map to the ones inferred by CaSQ. The tool is able to process large and complex maps built with CellDesigner (either following SBGN standards or not) and produce Boolean models in a standard output format, Systems Biology Marked Up Language-qualitative (SBML-qual), that can be further analyzed using popular modelling tools. References, annotations and layout of the CellDesigner molecular map are retained in the obtained model, facilitating interoperability and model reusability. AVAILABILITY AND IMPLEMENTATION:The present tool is available online: https://lifeware.inria.fr/?soliman/post/casq/ and distributed as a Python package under the GNU GPLv3 license. The code can be accessed here: https://gitlab.inria.fr/soliman/casq. SUPPLEMENTARY INFORMATION:Supplementary data are available at Bioinformatics online.
| S-EPMC7575051 | biostudies-literature
Project description:MotivationA plugin for the Java-based PathVisio pathway editor has been developed to help users draw diagrams of bioregulatory networks according to the Molecular Interaction Map (MIM) notation. Together with the core PathVisio application, this plugin presents a simple to use and cross-platform application for the construction of complex MIM diagrams with the ability to annotate diagram elements with comments, literature references and links to external databases. This tool extends the capabilities of the PathVisio pathway editor by providing both MIM-specific glyphs and support for a MIM-specific markup language file format for exchange with other MIM-compatible tools and diagram validation.AvailabilityThe PathVisio-MIM plugin is freely available and works with versions of PathVisio 2.0.11 and later on Windows, Mac OS X and Linux. Information about MIM notation and the MIMML format is available at http://discover.nci.nih.gov/mim. The plugin, along with diagram examples, instructions and Java source code, may be downloaded at http://discover.nci.nih.gov/mim/mim_pathvisio.html.
| S-EPMC3137219 | biostudies-literature
Project description:Functional neuroimaging studies are revealing the neural systems sustaining many sensory, motor and cognitive abilities. A proper understanding of these systems requires an appreciation of the degree to which they vary across subjects. Some sources of inter-subject variability might be easy to measure (demographics, behavioural scores, or experimental factors), while others are more difficult (cognitive strategies, learning effects, and other hidden sources). Here, we introduce a simple way of visualising whole-brain consistency and variability in brain responses across subjects using threshold-weighted voxel-based overlap maps. The output quantifies the proportion of subjects activating a particular voxel or region over a wide range of statistical thresholds. The sensitivity of our approach was assessed in 30 healthy adults performing a matching task with their dominant hand. We show how overlap maps revealed many effects that were only present in a subsample of our group; we discuss how overlap maps can provide information that may be missed or misrepresented by standard group analysis, and how this information can help users to understand their data. In particular, we emphasize that functional overlap maps can be particularly useful when it comes to explaining typical (or atypical) compensatory mechanisms used by patients following brain damage.
| S-EPMC4742862 | biostudies-other
Project description:Ligand docking at a protein site can be improved by prioritizing poses by similarity to validated binding modes found in the crystal structures of ligand/protein complexes. The interactions formed in the predicted model are searched in each of the reference 3D structures, taken individually. We propose to merge the information provided by all references, creating a single representation of all known binding modes. The method is called LID, an acronym for Local Interaction Density. LID was benchmarked in a pose prediction exercise on 19 proteins and 1382 ligands using PLANTS as docking software. It was also tested in a virtual screening challenge on eight proteins, with a dataset of 140,000 compounds from DUD-E and PubChem. LID significantly improved the performance of the docking program in both pose prediction and virtual screening. The gain is comparable to that obtained with a rescoring approach based on the individual comparison of reference binding modes (the GRIM method). Importantly, LID is effective with a small number of references. LID calculation time is negligible compared to the docking time.
| S-EPMC6681060 | biostudies-literature
Project description:Topographic maps in visual processing areas maintain the spatial order of the visual world. Molecular cues and neuronal activity both play critical roles in map formation, but their interaction remains unclear. Here, we demonstrate that when molecular- and activity-dependent cues are rendered nearly equal in force, they drive topographic mapping stochastically. The functional and anatomical representation of azimuth in the superior colliculus of heterozygous Islet2-EphA3 knockin (Isl2(EphA3/+)) mice is variable: maps may be single, duplicated, or a combination of the two. This heterogeneity is not due to genetic differences, since map organizations in individual mutant animals often differ between colliculi. Disruption of spontaneous waves of retinal activity resulted in uniform map organization in Isl2(EphA3/+) mice, demonstrating that correlated spontaneous activity is required for map heterogeneity. Computational modeling replicates this heterogeneity, revealing that molecular- and activity-dependent forces interact simultaneously and stochastically during topographic map formation.
| S-EPMC4583656 | biostudies-literature
Project description:The recently proposed concept of molecular connectivity maps enables researchers to integrate experimental measurements of genes, proteins, metabolites, and drug compounds under similar biological conditions. The study of these maps provides opportunities for future toxicogenomics and drug discovery applications. We developed a computational framework to build disease-specific drug-protein connectivity maps. We integrated gene/protein and drug connectivity information based on protein interaction networks and literature mining, without requiring gene expression profile information derived from drug perturbation experiments on disease samples. We described the development and application of this computational framework using Alzheimer's Disease (AD) as a primary example in three steps. First, molecular interaction networks were incorporated to reduce bias and improve relevance of AD seed proteins. Second, PubMed abstracts were used to retrieve enriched drug terms that are indirectly associated with AD through molecular mechanistic studies. Third and lastly, a comprehensive AD connectivity map was created by relating enriched drugs and related proteins in literature. We showed that this molecular connectivity map development approach outperformed both curated drug target databases and conventional information retrieval systems. Our initial explorations of the AD connectivity map yielded a new hypothesis that diltiazem and quinidine may be investigated as candidate drugs for AD treatment. Molecular connectivity maps derived computationally can help study molecular signature differences between different classes of drugs in specific disease contexts. To achieve overall good data coverage and quality, a series of statistical methods have been developed to overcome high levels of data noise in biological networks and literature mining results. Further development of computational molecular connectivity maps to cover major disease areas will likely set up a new model for drug development, in which therapeutic/toxicological profiles of candidate drugs can be checked computationally before costly clinical trials begin.
| S-EPMC2709445 | biostudies-literature
Project description:Lesion overlap difference maps have been used in studies designed to test anatomical hypotheses regarding brain systems critical for various cognitive and behavioral tasks, including naming and recognition of concrete entities [Damasio, H., Tranel, D., Grabowski, T., Adolphs, R., Damasio, A., 2004. Neural systems behind word and concept retrieval. Cognition 92, 179-229]. To date, the interpretation of these results has focused on areas of maximum lesion overlap differences. Here we explore formal methods for statistical thresholding and power analysis. We derive exact voxel-wise statistics describing the behavior of lesion overlap difference maps and lesion proportion difference maps under the null hypothesis of no association between lesion and deficit, and we apply the statistics to a large subset of the subjects previously reported in [Damasio, H., Tranel, D., Grabowski, T., Adolphs, R., Damasio, A., 2004. Neural systems behind word and concept retrieval. Cognition 92, 179-229], in order to reassess the lesion correlates of deficits in naming and recognition for five categories of concrete entities. The thresholded maps confirmed many of the results reported previously, but also revealed some differences. Differences in spatial distribution of the lesion correlates of impaired naming of unique versus nonunique entities were confirmed in the inferotemporal region (IT), although overlapping components across categories became apparent in left IT. Additionally, the left inferior frontal gyrus (IFG) was implicated in naming both categories of nonunique natural entities (animals and fruits/vegetables). In corresponding power analyses, we estimated where significant effects could be found under an assumption of maximal effect size given the observed spatial distribution of lesions. Such "effective coverage maps" are valuable for the interpretation of the results, notably because of heterogeneity in lesion coverage encountered in lesion studies. We strongly suggest that when inferential statistics are used in voxel-wise lesion-deficit statistical mapping, these or other power maps be included in the reports.
| S-EPMC2582202 | biostudies-literature