Wildfire: distributed, Grid-enabled workflow construction and execution

BACKGROUND: We observe two trends in bioinformatics: (i) analyses are increasing in complexity, often requiring several applications to be run as a workflow; and (ii) multiple CPU clusters and Grids are available to more scientists. The traditional solution to the problem of running workflows across multiple CPUs required programming, often in a scripting language such as perl. Programming places such solutions beyond the reach of many bioinformatics consumers. RESULTS: We present Wildfire, a graphical user interface for constructing and running workflows. Wildfire borrows user interface features from Jemboss and adds a drag-and-drop interface allowing the user to compose EMBOSS (and other) programs into workflows. For execution, Wildfire uses GEL, the underlying workflow execution engine, which can exploit available parallelism on multiple CPU machines including Beowulf-class clusters and Grids. CONCLUSION: Wildfire simplifies the tasks of constructing and executing bioinformatics workflows

ANTIHYPERGLYCEMIC AND ANTIHYPERLIPIDEMIC ACTIVITY OF JATROPHA GOSSYPIFOLIA METHANOLIC EXTRACT IN STREPTOZOTOCIN-NICOTINAMIDE INDUCED DIABETIC RATS

  Objective: The objective of the present study is to explore the antihyperglycemic and antihyperlipidemic activities of Jatropha gossypifolia methanolic extract (ME) in streptozotocin (STZ)-nicotinamide (NIC) induced diabetic model.Methods: Type II diabetes was induced by a single dose of NIC (110 mg/kg) and STZ (50 mg/kg b.w.) intraperitoneally. The diabetic animals were treated with ME (50 mg/kg and 100 mg/kg b.w.) of J. gossypifolia. At the end of experimental period, the effect of the ME on creatinine level, triglyceride (TG), total cholesterol (TC), high-density lipoprotein (HDL), low-density lipoprotein (LDL) and very LDL (VLDL) were analyzed. Liver function parameters such as glutamate oxaloacetate transaminase (GOT), glutamate pyruvate transaminase (GPT) were analyzed and liver glycogen content was estimated spectrophotometrically. After scarification of animals, the liver was collected and subjected to histopathology analysis. Glycogen content was estimated spectrophotometrically.Results: The ME treated diabetic rats showed a significant increase in HDL level and a decrease in creatinine, TG, TC, and VLDL levels. The treated group showed a significant decrease in liver function parameters such as GOT and GPT levels and significantly increased the liver glycogen content.Conclusion: These findings demonstrate that ME possess antihyperglycemic and antihyperlipidemic activity against STZ - NIC induced diabetic rats

Molecular mechanism of down-regulating adipogenic transcription factors in 3T3-L1 adipocyte cells by bioactive anti-adipogenic compounds

Obesity is growing at an alarming rate, which is characterized by increased adipose tissue. It increases the probability of many health complications, such as diabetes, arthritis, cardiac disease, and cancer. In modern society, with a growing population of obese patients, several individuals have increased insulin resistance. Herbal medicines are known as the oldest method of health care treatment for obesity-related secondary health issues. Several traditional medicinal plants and their effective phytoconstituents have shown anti-diabetic and anti adipogenic activity. Adipose tissue is a major site for lipid accumulation as well as the whole-body insulin sensitivity region. 3T3-L1 cell line model can achieve adipogenesis. Adipocyte characteristics features such as expression of adipocyte markers and aggregation of lipids are chemically induced in the 3T3-L1 fibroblast cell line. Differentiation of 3T3-L1 is an efficient and convenient way to obtain adipocyte like cells in experimental studies. Peroxisome proliferation activated receptor γ (PPARγ) and Cytosine-Cytosine-Adenosine Adenosine-Thymidine/Enhancer-binding protein α (CCAAT/Enhancer-binding protein α or C/EBPα) are considered to be regulating adipogenesis at the early stage, while adiponectin and fatty acid synthase (FAS) is responsible for the mature adipocyte formation. Excess accumulation of these adipose tissues and lipids leads to obesity. Thus, investigating adipose tissue development and the underlying molecular mechanism is important in the therapeutical approach. This review describes the cellular mechanism of 3T3-L1 fibroblast cells on potential anti-adipogenic herbal bioactive compounds

Exploration of Compost Soil for the Production of Thermo-Stable <i>Bacillus</i> Protease to Synthesize Bioactive Compounds through Soy Protein Hydrolysis

Application of bioactive peptides (BAPs) is promising due to their potential antimicrobial, antioxidant, agonistic, and ACE inhibition properties. To achieve a stable and active peptide at relatively high pH and temperatures by microbial fermentation, a wide variety of microorganisms need to be explored from diverse habitats, and compost is the excellent source. In an attempt to isolate potent protease-producing bacteria, gelatin-supplemented DM agar medium was used. Out of 140 pure cultures, initial protease production selects isolate D3L/1 (26 U/mL), and 16S rDNA sequencing confirmed it as Bacillus subtilis. Protease production was increased to 55.55 U/mL, with pH 7.5, 1% glucose, 1% casein, 1% ammonium sulfate, for 96 h of fermentation, at 37 °C under 140 rpm of shaking. Ion-exchange, and size-exclusion chromatography, 30 KDa protease was purified up to 4.1-fold (specific activity 3448.62 U/mL; 67.66% yield). The enzyme was active under broad temperatures (60 °C optimum), organic solvents, and pH variations. A total of 5% H2O2 can only reduce 40% of enzyme activity. However, 1 mM, Fe2+, and Cu2+ increased enzyme activity by five times. Soy hydrolysis (SPI) byD3L/1 protease produces bioactive compound (Serratia marcescens but active against Escherechia coli (47%), Staphylococcus aureus (28%), and Pseudomonas aeruginosa (12%)

Wildfire: distributed, Grid-enabled workflow construction and execution-5

<p><b>Copyright information:</b></p><p>Taken from "Wildfire: distributed, Grid-enabled workflow construction and execution"</p><p>BMC Bioinformatics 2005;6():69-69.</p><p>Published online 24 Mar 2005</p><p>PMCID:PMC1274263.</p><p>Copyright © 2005 Tang et al; licensee BioMed Central Ltd.</p> The components in this workflow are all custom applications, or custom scripts calling standard applications. Components format, group, join_scr and process_scr are administrative programs which translate and convert files from one format to another. Component rscript uses the R-project to cluster the amino acid sequences from a database of known allergens. For each cluster, we align its sequences and use a wavelet algorithm to predict motifs. The resulting motifs are used to construct HMM profiles using hmmbuild. Finally, we use these profiles with hmmpfam to predict allergenic sequences. Components join_scr and process_scr collate and summarise the results

Wildfire: distributed, Grid-enabled workflow construction and execution-4

<p><b>Copyright information:</b></p><p>Taken from "Wildfire: distributed, Grid-enabled workflow construction and execution"</p><p>BMC Bioinformatics 2005;6():69-69.</p><p>Published online 24 Mar 2005</p><p>PMCID:PMC1274263.</p><p>Copyright © 2005 Tang et al; licensee BioMed Central Ltd.</p>rallel within a parallel for loop. The circle denotes a while loop, with test as loop guard: if test returns false, then we follow the bottom branch to extract, otherwise we follow the right branch and test test again after reassign. Component eval2 is executed in parallel once for each file matching follower_sol*

Wildfire: distributed, Grid-enabled workflow construction and execution-0

<p><b>Copyright information:</b></p><p>Taken from "Wildfire: distributed, Grid-enabled workflow construction and execution"</p><p>BMC Bioinformatics 2005;6():69-69.</p><p>Published online 24 Mar 2005</p><p>PMCID:PMC1274263.</p><p>Copyright © 2005 Tang et al; licensee BioMed Central Ltd.</p>ation which allows users to construct workflows using a drawing analogy. Wildfire executes the workflow by exporting it as a GEL script which is executed using a suitable GEL interpretor. There are GEL interpretors for execution on (i) the Grid, using Condor, (ii) a cluster, using LSF, PBS or SGE, and (iii) the same machine, which could be a laptop, desktop or multi-processor server