共查询到20条相似文献，搜索用时 15 毫秒
1.
Dennis YQ Wang Luca Cardelli Andrew Phillips Nir Piterman Jasmin Fisher 《BMC systems biology》2009,3(1):118-17
Background
The epidermal growth factor receptor (EGFR) signaling pathway plays a key role in regulation of cellular growth and development. While highly studied, it is still not fully understood how the signal is orchestrated. One of the reasons for the complexity of this pathway is the extensive network of inter-connected components involved in the signaling. In the aim of identifying critical mechanisms controlling signal transduction we have performed extensive analysis of an executable model of the EGFR pathway using the stochastic pi-calculus as a modeling language. 相似文献2.
Background
An important emerging trend in the analysis of microarray data is to incorporate known pathway information a priori. Expression level "summaries" for pathways, obtained from the expression data for the genes constituting the pathway, permit the inclusion of pathway information, reduce the high dimensionality of microarray data, and have the power to elucidate gene-interaction dependencies which are not already accounted for through known pathway identification. 相似文献3.
Background
Once a new genome is sequenced, one of the important questions is to determine the presence and absence of biological pathways. Analysis of biological pathways in a genome is a complicated task since a number of biological entities are involved in pathways and biological pathways in different organisms are not identical. Computational pathway identification and analysis thus involves a number of computational tools and databases and typically done in comparison with pathways in other organisms. This computational requirement is much beyond the capability of biologists, so information systems for reconstructing, annotating, and analyzing biological pathways are much needed. We introduce a new comparative pathway analysis workbench, ComPath, which integrates various resources and computational tools using an interactive spreadsheet-style web interface for reliable pathway analyses. 相似文献4.
Paschall JE Oleksiak MF VanWye JD Roach JL Whitehead JA Wyckoff GJ Kolell KJ Crawford DL 《BMC genomics》2004,5(1):96
Background
While studies of non-model organisms are critical for many research areas, such as evolution, development, and environmental biology, they present particular challenges for both experimental and computational genomic level research. Resources such as mass-produced microarrays and the computational tools linking these data to functional annotation at the system and pathway level are rarely available for non-model species. This type of "systems-level" analysis is critical to the understanding of patterns of gene expression that underlie biological processes. 相似文献5.
Marinus FW te Pas Ina Hulsegge Albart Coster Marco H Pool Henri H Heuven Luc LG Janss 《BMC developmental biology》2007,7(1):66
Background
Combining microarray results and biological pathway information will add insight into biological processes. Pathway information is widely available in databases through the internet. 相似文献6.
Background
The rapidly evolving discipline of biological and biomedical engineering requires adaptive instructional approaches that teach students to target and solve multi-pronged and ill-structured problems at the cutting edge of scientific research. Here we present a modular approach to designing a lab-based course in the emerging field of biofabrication and biological design, leading to a final capstone design project that requires students to formulate and test a hypothesis using the scientific method.Results
Students were assessed on a range of metrics designed to evaluate the format of the course, the efficacy of the format for teaching new topics and concepts, and the depth of the contribution this course made to students training for biological engineering careers. The evaluation showed that the problem-based format of the course was well suited to teaching students how to use the scientific method to investigate and uncover the fundamental biological design rules that govern the field of biofabrication.Conclusions
We show that this approach is an efficient and effective method of translating emergent scientific principles from the lab bench to the classroom and training the next generation of biological and biomedical engineers for careers as researchers and industry practicians.7.
Background
The topology of a biological pathway provides clues as to how a pathway operates, but rationally using this topology information with observed gene expression data remains a challenge. 相似文献8.
Background
Reconstruction of biological pathways is typically done through mapping well-characterized pathways of model organisms to a target genome, through orthologous gene mapping. A limitation of such pathway-mapping approaches is that the mapped pathway models are constrained by the composition of the template pathways, e.g., some genes in a target pathway may not have corresponding genes in the template pathways, the so-called “missing gene” problem.Methods
We present a novel pathway-expansion method for identifying additional genes that are possibly involved in a target pathway after pathway mapping, to fill holes caused by missing genes as well as to expand the mapped pathway model. The basic idea of the algorithm is to identify genes in the target genome whose homologous genes share common operons with homologs of any mapped pathway genes in some reference genome, and to add such genes to the target pathway if their functions are consistent with the cellular function of the target pathway.Results
We have implemented this idea using a graph-theoretic approach and demonstrated the effectiveness of the algorithm on known pathways of E. coli in the KEGG database. On all KEGG pathways containing at least 5 genes, our method achieves an average of 60% positive predictive value (PPV) and the performance is increased with more seed genes added. Analysis shows that our method is highly robust.Conclusions
An effective method is presented to find missing genes in biological pathways of prokaryotes, which achieves high prediction reliability on E. coli at a genome level. Numerous missing genes are found to be related to knwon E. coli pathways, which can be further validated through biological experiments. Overall this method is robust and can be used for functional inference.9.
Background
There is general agreement amongst biologists about the need for good pathway diagrams and a need to formalize the way biological pathways are depicted. However, implementing and agreeing how best to do this is currently the subject of some debate. 相似文献10.
11.
Background
Substantial amounts of data on cell signaling, metabolic, gene regulatory and other biological pathways have been accumulated in literature and electronic databases. Conventionally, this information is stored in the form of pathway diagrams and can be characterized as highly "compartmental" (i.e. individual pathways are not connected into more general networks). Current approaches for representing pathways are limited in their capacity to model molecular interactions in their spatial and temporal context. Moreover, the critical knowledge of cause-effect relationships among signaling events is not reflected by most conventional approaches for manipulating pathways. 相似文献12.
Background
The identification of potentially relevant biomarkers and a deeper understanding of molecular mechanisms related to heart failure (HF) development can be enhanced by the implementation of biological network-based analyses. To support these efforts, here we report a global network of protein-protein interactions (PPIs) relevant to HF, which was characterized through integrative bioinformatic analyses of multiple sources of "omic" information. 相似文献13.
Background
Growing interest on biological pathways has called for new statistical methods for modeling and testing a genetic pathway effect on a health outcome. The fact that genes within a pathway tend to interact with each other and relate to the outcome in a complicated way makes nonparametric methods more desirable. The kernel machine method provides a convenient, powerful and unified method for multi-dimensional parametric and nonparametric modeling of the pathway effect. 相似文献14.
Tsutomu Matsunaga Chikara Yonemori Etsuji Tomita Masaaki Muramatsu 《BMC bioinformatics》2009,10(1):205-9
Background
Progress in the life sciences cannot be made without integrating biomedical knowledge on numerous genes in order to help formulate hypotheses on the genetic mechanisms behind various biological phenomena, including diseases. There is thus a strong need for a way to automatically and comprehensively search from biomedical databases for related genes, such as genes in the same families and genes encoding components of the same pathways. Here we address the extraction of related genes by searching for densely-connected subgraphs, which are modeled as cliques, in a biomedical relational graph. 相似文献15.
Ana P Teixeira Carlos Alves Paula M Alves Manuel JT Carrondo Rui Oliveira 《BMC bioinformatics》2007,8(1):30
Background
The progress in the "-omic" sciences has allowed a deeper knowledge on many biological systems with industrial interest. This knowledge is still rarely used for advanced bioprocess monitoring and control at the bioreactor level. In this work, a bioprocess control method is presented, which is designed on the basis of the metabolic network of the organism under consideration. The bioprocess dynamics are formulated using hybrid rigorous/data driven systems and its inherent structure is defined by the metabolism elementary modes. 相似文献16.
Alexandre Tromas Nils Braun Philippe Muller Tatyana Khodus Ivan A. Paponov Klaus Palme Karin Ljung Ji-Young Lee Philip Benfey James A. H. Murray Ben Scheres Catherine Perrot-Rechenmann 《PloS one》2009,4(9)
Background
In plants, the phytohormone auxin is a crucial regulator sustaining growth and development. At the cellular level, auxin is interpreted differentially in a tissue- and dose-dependent manner. Mechanisms of auxin signalling are partially unknown and the contribution of the AUXIN BINDING PROTEIN 1 (ABP1) as an auxin receptor is still a matter of debate.Methodology/Principal Findings
Here we took advantage of the present knowledge of the root biological system to demonstrate that ABP1 is required for auxin response. The use of conditional ABP1 defective plants reveals that the protein is essential for maintenance of the root meristem and acts at least on the D-type CYCLIN/RETINOBLASTOMA pathway to control entry into the cell cycle. ABP1 affects PLETHORA gradients and confers auxin sensitivity to root cells thus defining the competence of the cells to be maintained within the meristem or to elongate. ABP1 is also implicated in the regulation of gene expression in response to auxin.Conclusions/Significance
Our data support that ABP1 is a key regulator for root growth and is required for auxin-mediated responses. Differential effects of ABP1 on various auxin responses support a model in which ABP1 is the major regulator for auxin action on the cell cycle and regulates auxin-mediated gene expression and cell elongation in addition to the already well known TIR1-mediated ubiquitination pathway. 相似文献17.
18.
Hiroshi Tsugawa Yuki Tsujimoto Masanori Arita Takeshi Bamba Eiichiro Fukusaki 《BMC bioinformatics》2011,12(1):131
Background
The goal of metabolomics analyses is a comprehensive and systematic understanding of all metabolites in biological samples. Many useful platforms have been developed to achieve this goal. Gas chromatography coupled to mass spectrometry (GC/MS) is a well-established analytical method in metabolomics study, and 200 to 500 peaks are routinely observed with one biological sample. However, only ~100 metabolites can be identified, and the remaining peaks are left as "unknowns". 相似文献19.
Takashi Murakami Yoichi Akazawa Noboru Yatagai Takafumi Hiromoto Noriko Sasahara Tsuyoshi Saito Naoto Sakamoto Akihito Nagahara Takashi Yao 《Diagnostic pathology》2018,13(1):88
Background
Colorectal sessile serrated adenoma/polyps (SSA/Ps) are considered early precursor lesions in the serrated neoplasia pathway. Recent studies have shown associations of SSA/Ps with lost MLH1 expression, a CpG island methylator phenotype, and BRAF mutations. However, the molecular biological features of SSA/Ps with early neoplastic progression have not yet been fully elucidated, owing to the rarity of cases of SSA/P with advanced histology such as cytologic dysplasia or invasive carcinoma. In this study, we aimed to elucidate the molecular biological features of SSA/Ps with dysplasia/carcinoma, representing relatively early stages of the serrated neoplasia pathway.Methods
We performed immunostaining for β-catenin, MLH1, and mucins (e.g., MUC2, MUC5AC, MUC6, and CD10); targeted next-generation sequencing; and microsatellite instability (MSI) testing in 8 SSA/P lesions comprised of 4 SSA/Ps with high-grade dysplasia and 4 SSA/Ps with submucosal carcinoma.Results
Lost MLH1 expression was found in 5 cases. All lesions studied were positive for nuclear β-catenin expression. Regarding phenotypic mucin expression, all lesions were positive for MUC2, but negative for CD10. MUC5AC and MUC6 positivity was observed in 7 cases. Genetically, the most frequently mutated gene was BRAF (7 cases), and other mutations were detected in FBXW7 (3 cases); TP53 (2 cases), and KIT, PTEN, SMAD4, and SMARCB1 (1 case each). Furthermore, 4 of 8 lesions were MSI-high and the remaining 4 lesions were microsatellite-stable (MSS). Interestingly, all 4 MSI-high lesions displayed MLH1 loss, 3 of which harbored a FBXW7 mutation, but not a TP53 mutation. However, 2 MSS lesions harbored a TP53 mutation, although none harbored a FBXW7 mutation.Conclusions
SSA/Ps with dysplasia/carcinoma frequently harbored BRAF mutations. Activation of the WNT/β-catenin signaling pathway may facilitate the development of dysplasia in SSA/Ps and progression to carcinoma. Furthermore, our results suggested that these lesions might be associated with both MSI-high and MSS colorectal cancer, which might be distinguished by distinct molecular biological features such as lost MLH1 expression, FBXW7 mutations, and TP53 mutations.20.