144 research outputs found
lusystemsbio/NetAct: NetAct R Package
No full textNetAct a computational platform for constructing core transcription-factor regulatory networks using both transcriptomics data and literature-based transcription factor-target databases. NetAct robustly infers the activities of regulators using target expression, constructs networks based on transcriptional activity, and integrates mathematical modeling for validation.
NetAct is licensed under the MIT License https://github.com/lusystemsbio/NetAct/blob/master/LICENSE
Authors:
Kenong Su [email protected],
Vivek Kohar [email protected],
Danya Gordin [email protected] (Main maintainer),
Mingyang Lu [email protected]
from the Lu lab @ Northeastern University https://lusystemsbio.northeastern.edu/.
Installation:
library(devtools)
install_github("lusystemsbio/NetAct", dependencies=T, build_vignettes = T)
Tutorial:
https://htmlpreview.github.io/?https://github.com/lusystemsbio/NetAct/blob/master/vignettes/Tutorial.html
Manual:
https://github.com/lusystemsbio/NetAct/blob/master/vignettes/NetAct_1.0.5.pdf
Reference:
Kenong Su, Ataur Katebi, Vivek Kohar, Benjamin Clauss, Danya Gordin, Zhaohui S. Qin, R. Krishna M. Karuturi, Sheng Li, Mingyang Lu. NetAct: a computational platform to construct core transcription factor regulatory networks using gene activity. bioRxiv 2022.05.06.487898; doi: https://doi.org/10.1101/2022.05.06.48789
Knowledge representation within information systems in manufacturing environments
No full textThis thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Representing knowledge as information content alone is insufficient in providing us with an understanding of the world around us. A combination of context as well as reasoning of the information content is fundamental to representing knowledge in an information system. Knowledge Representation is typically concerned with providing structures and theories that are used as a basis for intelligent reasoning. For this research however, the author defines an alternative meaning, which is related to how knowledge is used in a given context. Thus, this dissertation provides a contribution to the field of knowledge within information systems, in terms of the development of a frame-of-reference that will support the reader in navigating through the different forms of explicit and tacit knowledge use within the manufacturing industry. In doing so, the dissertation also presents the generation of a novel classification of three forms of knowledge (Structural, Interpretive and Evaluative forms); the development of a conceptual framework which highlights the drivers for knowledge transformation; and the development of a conceptual model which seeks to envelop both the content as well as the context of knowledge (Semiotic as well as Symbiotic factors). This is established through the use of an Empirical, Quantitative case study approach, that seeks to explore an interpretivist view of knowledge representation within two information systems contexts, within two UK manufacturing organisations. The first case study presents how a-priori knowledge assumptions are used in a computer aided engineering decision-making task within a high technology manufacturing company. The second case study shows how knowledge is used within the IT/IS investment evaluation decision making process, within a manufacturing SME. In doing so, both case studies attempt to elucidate the inherent, underlying relationship between explicit and tacit knowledge, via a frame-of-reference developed by the author which defines key drivers for knowledge transformation
Summary of the First Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE1)
No full textChallenges related to development, deployment, and maintenance of reusable software for science are becoming a growing concern. Many scientists’ research increasingly depends on the quality and availability of software upon which their works are built. To highlight some of these issues and share experiences, the First Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE1) was held in November 2013 in conjunction with the SC13 Conference. The workshop featured keynote presentations and a large number (54) of solicited extended abstracts that were grouped into three themes and presented via panels. A set of collaborative notes of the presentations and discussion was taken during the workshop.
Unique perspectives were captured about issues such as comprehensive documentation, development and deployment practices, software licenses and career paths for developers. Attribution systems that account for evidence of software contribution and impact were also discussed. These include mechanisms such as Digital Object Identifiers, publication of “software papers”, and the use of online systems, for example source code repositories like GitHub. This paper summarizes the issues and shared experiences that were discussed, including cross-cutting issues and use cases. It joins a nascent literature seeking to understand what drives software work in science, and how it is impacted by the reward systems of science. These incentives can determine the extent to which developers are motivated to build software for the long-term, for the use of others, and whether to work collaboratively or separately. It also explores community building, leadership, and dynamics in relation to successful scientific software
Autonomous capillary systems for life science research and medical diagnostics
No full textIn autonomous capillary systems (CS) minute amounts of liquid are transported owing to capillary forces. Such CSs are appealing due to their portability, flexibility, and the exceptional physical behavior of liquids in micrometer sized microchannels, in particular, capillarity and short diffusion times. CSs have shown to be a promising technology for miniaturized immunoassays in life science research and diagnostics. Building on existing experimental demonstrations of immunoassays in CSs, a theoretical model of such immunoassays is implemented, tools and CSs for performing immunoassays are developed, key functional elements of CSs such as capillary pumps and valves are explored experimentally, and a proof-of-concept of the ultimate goal of one-step immunoassays are given in this work.
For the theoretical modeling of immunoassays in CSs a finite difference algorithm is applied to delineate the role of the transport of analyte molecules in the microchannel (convection and diffusion), the kinetics of binding between the analyte and the capture antibodies, and the surface density of the capture antibody on the assay. The model shows that assays can be greatly optimized by varying the flow velocity of the solution of analyte in the microchannels. The model also shows how much the analyte-antibody binding constant and the surface density of the capture antibodies influence the performance of the assay. We derive strategies to optimize assays toward maximal sensitivity, minimal sample volume requirement or fast performance.
A method using evaporation for controlling the flow rate in CSs was developed for maximum flexibility for developing assays. The method allows to use small CSs that initially are filled by capillary forces and then provide a well defined area of the liquid-air interface from which liquid can evaporate. Temperature and humidity are continuously measured and Peltier-elements are used to adjust the temperatures in multiple areas of the CSs relative to the dew-point. Thereby flow rates in the range from ~1.2 nL s−1 to ~30 pL s−1 could be achieved in the microchannels. This method was then used for screening cells for surface receptors.
CSs, that do not need any peripherals for controlling flow rates become even more appealing. We explored the filling behavior of such CSs having microchannels of various length and large capillary pumps. The capillary pumps comprise microstructures of various sizes and shapes, which are spaced to encode certain capillary pressures. The spacing and shape of the microstructures is also used to orient the filling front to obtain a reliable filling behavior and to minimize the risk of entrapping air. We show how two capillary pumps having different hydrodynamic properties can be connected to program a sequence of slow and fast flow rates in CSs. Liquid filling CSs can hardly be stopped, but in some cases it might be beneficial to do so. In a separate chapter we explore how microstructures need to be designed to use capillary forces to stop, time, or trigger liquids.
Besides well-defined flow rates in CSs accurately patterned capture antibodies (cAbs) are key for performing high-sensitive surface immunoassays in CSs. We present a method compatible with mass fabrication for patterning cAbs in dense lines of up to 8 lines per millimeter. These cAbs are used with CSs that are optimized for convenient handling, pipetting of solutions, pumping of liquids such as human serum, and visualization of signals for fluorescence immunoassays to detect c-reactive protein (CRP) with a sensitivity of 0.9 ng mL−1 (7.8 pM) from 1 uL of CRP-spiked human serum, within 11 minutes, with 4 pipetting steps, and a total volume of sample and reagents of <1.5 uL.
CSs for diagnostic applications have different requirements than CSs that are used as a research tool in life sciences, where a high flexibility and performance primes over the ease of use and portability of the CSs. We give a proof-of-concept for one-step immunoassays based on CSs which we think can be the base for developing portable diagnostics for point-of-care applications. All reagents are preloaded in the CSs. A sample loaded in the CSs redissolves and reconstitutes the detection antibodies (dAbs), analyte-dAb-complexes are formed and detected downstream in the CSs. A user only needs to load a sample and measure the result using a fluorescence microscope or scanner. C-reactive protein was detected in human serum at clinical concentrations within 10 minutes and using only 2 uL of sample
Migration and separation in structured microfluidic systems
No full textBogunovic L. Migration and separation in structured microfluidic systems. Bielefeld: Bielefeld University; 2013.Spatially structured microfluidic channels in a state far from thermal equilibrium have been developed to address three fundamental problems in modern (bio-)analytics: the usually fixed separation criterion (e.g. a gel density is not changeable on the fly), the usually unknown polarizability properties of samples for dielectrophoretic manipulation and the requirement of a specifically designed chiral selector for chiral separation.
1) Typical biotechnological separation techniques like filters, chromatography, or gel electrophoresis have a fixed implemented separation criterion, e.g. defined by pore size, affinity of the steady phase, or gel density. To overcome this limit, the aim of the first project is the development and functional characterization of a microfluidic ratchet device with a dynamically changeable separation criterion. Depending on the applied voltage scheme, an arbitrarily selectable sub-group of the available species in the analyte solution is forced to migrate into opposite direction than the remaining species. Changing the voltage scheme will immediately switch the separation criterion. The device is based on a sophisticated interplay between electrophoresis and dielectrophoresis and operates with any charged and polarizable material in solution such as e.g. micro- and nanoparticles, cells, or biomolecules.
2) Many microfluidic systems rely on dielectrophoresis to immobilize, manipulate, or sort a somehow polarizable sample. However, the actual polarizability value usually remains unknown and appropriate electric fields to trigger dielectrophoresis are found via trial and error. The second project uses dielectrophoretic traps in a tilted potential implemented in a microfluidic channel to automatically quantify single molecule (here DNA) polarizabilities via fluorescence video microscopy. The approach is tested by reproducing a well-known scaling law between the buffer solution’s ionic strength and the polarizability for two different DNA types. In a second experiment the influence of the required fluorescence staining on the polarizability is investigated. Besides the pure quantification of polarizability in basic research, this system could be used to automatically tune dielectrophoretic traps in a final product to broaden its range of possible analyte classes.
3)When chiral molecules are about to be separated after synthesis, a chromatography setup is used which typically requires chiral selection or derivatization agents. Usually these chemicals have to be redeveloped for every new analyte. The third project’s aim is the implementation of a generic and continuously operating principle to separate chiral molecules in microfluidic channels without the need for any chiral selection or derivatization agent. Two conceptually different microfluidic approaches with excellent sorting performance were developed and experimentally evaluated. Following Curie’s principle, both approaches rely on microfluidic structures that somehow break the symmetry in the channel in every relevant dimension. Injected model enantiomers are demonstrated to split up according to their chirality and to accumulate near opposite channel walls
Neural Functions Play Different Roles in Triple Negative Breast Cancer (TNBC) and non-TNBC
No full textTriple negative breast cancer (TNBC) represents the most malignant subtype of breast cancer, and yet our understanding about its unique biology remains elusive. We have conducted a comparative computational analysis of transcriptomic data of TNBC and non-TNBC (NTNBC) tissue samples from the TCGA database, focused on genes involved in neural functions. Our main discoveries are: (1) while both subtypes involve neural functions, TNBC has substantially more up-regulated neural genes than NTNBC, suggesting that TNBC is more complex than NTNBC; (2) non-neural functions related to cell-microenvironment interactions and intracellular damage processing are key inducers of the neural genes in both TNBC and NTNBC, but the inducer-responder relationships are different in the two cancer subtypes; (3) key neural functions such as neural crest formation are predicted to enhance adaptive immunity in TNBC while glia development, along with a few other neural functions, induce both innate and adaptive immunity in NTNBC. These results reveal key differences in the biology between the two cancer subtypes, particularly in terms of the roles that neural functions play. Our findings may open new doors for further investigation of the distinct biology of TNBC vs. NTNBC.The authors thank Professor Sha Cao of Indiana University Biostatistics Department for the advice regarding data analytics. The senior author thanks the financial support from both Georgia Research Alliance and the China-Japan Union Hospital of Jilin University
Nonlinear dimension reduction and clustering by Minimum Curvilinearity unfold neuropathic pain and tissue embryological classes
No full textMotivation: Nonlinear small datasets, which are characterized by low numbers of samples and very high numbers of measures, occur frequently in computational biology, and pose problems in their investigation. Unsupervised hybrid-two-phase (H2P) procedures-specifically dimension reduction (DR), coupled with clustering-provide valuable assistance, not only for unsupervised data classification, but also for visualization of the patterns hidden in high-dimensional feature space. Methods: 'Minimum Curvilinearity' (MC) is a principle that-for small datasets-suggests the approximation of curvilinear sample distances in the feature space by pair-wise distances over their minimum spanning tree (MST), and thus avoids the introduction of any tuning parameter. MC is used to design two novel forms of nonlinear machine learning (NML): Minimum Curvilinear embedding (MCE) for DR, and Minimum Curvilinear affinity propagation (MCAP) for clustering. Results: Compared with several other unsupervised and supervised algorithms, MCE and MCAP, whether individually or combined in H2P, overcome the limits of classical approaches. High performance was attained in the visualization and classification of: (i) pain patients (proteomic measurements) in peripheral neuropathy; (ii) human organ tissues (genomic transcription factor measurements) on the basis of their embryological origin. Conclusion: MC provides a valuable framework to estimate nonlinear distances in small datasets. Its extension to large datasets is prefigured for novel NMLs. Classification of neuropathic pain by proteomic profiles offers new insights for future molecular and systems biology characterization of pain. Improvements in tissue embryological classification refine results obtained in an earlier study, and suggest a possible reinterpretation of skin attribution as mesodermal. © The Author(s) 2010. Published by Oxford University Press
A network-based multi-target computational estimation scheme for anticoagulant activities of compounds.
No full textBACKGROUND: Traditional virtual screening method pays more attention on predicted binding affinity between drug molecule and target related to a certain disease instead of phenotypic data of drug molecule against disease system, as is often less effective on discovery of the drug which is used to treat many types of complex diseases. Virtual screening against a complex disease by general network estimation has become feasible with the development of network biology and system biology. More effective methods of computational estimation for the whole efficacy of a compound in a complex disease system are needed, given the distinct weightiness of the different target in a biological process and the standpoint that partial inhibition of several targets can be more efficient than the complete inhibition of a single target. METHODOLOGY: We developed a novel approach by integrating the affinity predictions from multi-target docking studies with biological network efficiency analysis to estimate the anticoagulant activities of compounds. From results of network efficiency calculation for human clotting cascade, factor Xa and thrombin were identified as the two most fragile enzymes, while the catalytic reaction mediated by complex IXa:VIIIa and the formation of the complex VIIIa:IXa were recognized as the two most fragile biological matter in the human clotting cascade system. Furthermore, the method which combined network efficiency with molecular docking scores was applied to estimate the anticoagulant activities of a serial of argatroban intermediates and eight natural products respectively. The better correlation (r = 0.671) between the experimental data and the decrease of the network deficiency suggests that the approach could be a promising computational systems biology tool to aid identification of anticoagulant activities of compounds in drug discovery. CONCLUSIONS: This article proposes a network-based multi-target computational estimation method for anticoagulant activities of compounds by combining network efficiency analysis with scoring function from molecular docking
EDGAR: a software framework for the comparative analysis of prokaryotic genomes
No full textBlom J, Albaum S, Doppmeier D, et al. EDGAR: a software framework for the comparative analysis of prokaryotic genomes. BMC Bioinformatics. 2009;10(1): 154.Background:The introduction of next generation sequencing approaches has caused a rapid increase in the number of completely sequenced genomes. As one result of this development, it is now feasible to analyze large groups of related genomes in a comparative approach. A main task in comparative genomics is the identification of orthologous genes in different genomes and the classification of genes as core genes or singletons. Results: To support these studies EDGAR – ''Efficient Database framework for comparative Genome Analyses using BLAST score Ratios'' – was developed. EDGAR is designed to automatically perform genome comparisons in a high throughput approach. Comparative analyses for 582 genomes across 75 genus groups taken from the NCBI genomes database were conducted with the software and the results were integrated into an underlying database. To demonstrate a specific application case, we analyzed ten genomes of the bacterial genus Xanthomonas, for which phylogenetic studies were awkward due to divergent taxonomic systems. The resultant phylogeny EDGAR provided was consistent with outcomes from traditional approaches performed recently and moreover, it was possible to root each strain with unprecedented accuracy. Conclusion: EDGAR provides novel analysis features and significantly simplifies the comparative analysis of related genomes. The software supports a quick survey of evolutionary relationships and simplifies the process of obtaining new biological insights into the differential gene content of kindred genomes. Visualization features, like synteny plots or Venn diagrams, are offered to the scientific community through a web-based and therefore platform independent user interface http://edgar.cebitec.uni-bielefeld.de webcite, where the precomputed data sets can be browsed
Rational Design of an Ultrasensitive Quorum-Sensing Switch
No full textOne of the purposes of synthetic biology is to develop rational methods that accelerate the design of genetic circuits, saving time and effort spent on experiments and providing reliably predictable circuit performance. We applied a reverse engineering approach to design an ultrasensitive transcriptional quorum-sensing switch. We want to explore how systems biology can guide synthetic biology in the choice of specific DNA sequences and their regulatory relations to achieve a targeted function. The workflow comprises network enumeration that achieves the target function robustly, experimental restriction of the obtained candidate networks, global parameter optimization via mathematical analysis, selection and engineering of parts based on these calculations, and finally, circuit construction based on the principles of standardization and modularization. The performance of realized quorum-sensing switches was in good qualitative agreement with the computational predictions. This study provides practical principles for the rational design of genetic circuits with targeted functions.National Natural Science Foundation of China [11434001]; Ministry of Science and Technology of China [2012AA02A702]SCI(E)ARTICLE81445-1452
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