Top PDF Tools For Spatiotemporally Specific Proteomic Analysis In Multicellular Organisms

Tools For Spatiotemporally Specific Proteomic Analysis In Multicellular Organisms

Tools For Spatiotemporally Specific Proteomic Analysis In Multicellular Organisms

Cell-selective metabolic labeling of proteins with functionalizable amino acids is a promising method to precisely interrogate protein synthesis in a living animal with- out dissection. Because labeled proteins – and only labeled proteins – are subject to conjugation to affinity probes, proteins from targeted cells can be separated from the rest of the organism and identified by mass spectrometry. This potentially pow- erful technique operates on the premise that restricting expression of engineered aminoacyl-tRNA synthetases with promoters active only in specific cells restricts la- beling to those cells. For example, Chin and coworkers used the germline-specific driver GAL4::VP16-nos.UTR in combination with an engineered Methanosarcina prroylysyl-tRNA synthetase/tRNA pair to identify proteins synthesized in germ cells of the Drosophila ovary [118]. Dieterich and coworkers used the motor neuron-specific driver OK371-GAL4 in combination with an engineered Drosophila methionyl-tRNA synthetase to monitor differences in protein synthesis rates in motor neurons in a fly model for Charcot-Marie-Tooth neuropathy [143, 144]. We have used the pharyn- geal muscle-specific driver myo-2 5 in combination with an engineered Caenorhabditis phenylalanyl-tRNA synthetase to discover previously unidentified pharyngeal-muscle- specific calponin-like proteins [145]. However in a multicellular organism, many cells cannot be targeted with a single promoter. Frequently, cell- and time-specific ex- pression arises from the combinatorial action of multiple regulators. To overcome the limitations of single-component systems for cell-selective metabolic labeling of proteins, we have developed a two-component system based on split-intein-mediated reconstitution of a split-aminoacyl-tRNA synthetase (Figure 3.1).
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Testing ecological theories with sequence similarity networks: marine ciliates exhibit similar geographic dispersal patterns as multicellular organisms

Testing ecological theories with sequence similarity networks: marine ciliates exhibit similar geographic dispersal patterns as multicellular organisms

Phylogenetic analysis of short read data has made great strides in recent years, following the development of phylogenetic placement algorithms for incorporating short read data into a reference phylogeny (for example, [44,45]). Yet, multiple alignments and tree reconstructions with hundreds of thousands to millions of environmental sequences from HTS are either slow (when accurate) or inaccurate (when fast) [44]. Furthermore, a challenge in such tools still consists in developing appropriate visualization tools and metrics for analyzing distributions of reads on computed trees [44]. The network approach offers a powerful alternative in terms of comparative and visualization strategies (Figure 1), with the benefit of intro- ducing several informative graph-based estimates describ- ing the relationships between sequences (Table 1), thereby offering independent ways of analyzing the distribution of microbial organisms. In other words, sequence similarity networks allow the empirical testing of aspects of the theoretical framework of microbial ecology through the exploitation of network-based properties (Table 1).
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The meaning of death : evolution and ecology of apoptosis in protozoan parasites

The meaning of death : evolution and ecology of apoptosis in protozoan parasites

Abstract: The discovery that an apoptosis-like, pro- grammed cell death (PCD) occurs in a broad range of protozoan parasites offers novel therapeutic tools to treat some of the most serious infectious diseases of humans, companion animals, wildlife, and livestock. Whilst apop- tosis is an essential part of normal development, maintenance, and defence in multicellular organisms, its occurrence in unicellular parasites appears counter- intuitive and has proved highly controversial: according to the Darwinian notion of ‘‘survival of the fittest’’, parasites are expected to evolve strategies to maximise their proliferation, not death. The prevailing, and untest- ed, opinion in the literature is that parasites employ apoptosis to ‘‘altruistically’’ self-regulate the intensity of infection in the host/vector. However, evolutionary theory tells us that at most, this can only be part of the explanation, and other non-mutually exclusive hypothe- ses must also be tested. Here, we explain the evolutionary concepts that can explain apoptosis in unicellular parasites, highlight the key questions, and outline the approaches required to resolve the controversy over whether parasites ‘‘commit suicide’’. We highlight the need for integration of proximate and functional ap- proaches into an evolutionary framework to understand apoptosis in unicellular parasites. Understanding how, when, and why parasites employ apoptosis is central to targeting this process with interventions that are sustain- able in the face of parasite evolution.
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Mosaic physiology from developmental noise: within organism physiological diversity as an alternative to phenotypic plasticity and phenotypic flexibility

Mosaic physiology from developmental noise: within organism physiological diversity as an alternative to phenotypic plasticity and phenotypic flexibility

Testing the mosaic physiology hypothesis will be non-trivial. So far, the functional diversification of clonal lineages has simply been observed, and, in some unicellular studies, has been related to fitness (Samoilov et al., 2006). To test whether mosaic physiology really occurs in multicellular organisms and, further, whether it can be adaptive, will require a new research program. The first step should be to assess levels of functional diversity among cells within tissues and organs, and whether that diversity affects tissue- and organ-level function. Such an effort will require substantial advances in experimental techniques for measuring organ phenotypes at multiple levels – e.g. among multiple cells and for whole organs – simultaneously. The second step will be to determine whether functional diversity within tissues and organs actually stems from developmental stochasticity or from other, more deterministic developmental events. There are now well-established methods for unicells that allow one to visualize stochasticity in the expression levels of individual messages and proteins, and these are beginning to be applied to metazoans. The next steps will be to apply these techniques to multicellular organisms across multiple developmental stages. In addition, there is the recurring problem of linking up stochasticity in individual molecules to stochasticity in function. Third, we need to be able to experimentally manipulate levels of stochasticity, and thereby degrees of functional diversity, in tissues. Such an approach likely will work best when levels of stochasticity in individual genes can be manipulated, e.g. by modifying their promoters or locations in the genome. Finally, established methods for manipulating stochasticity will allow us to examine links between mosaic physiology and fitness. In particular, levels of mosaic plasticity should be altered and effects on fitness measured, especially across environments having different magnitudes and kinds of variation. In general, the steps outlined above probably will be possible soonest in model metazoans such as flies and nematodes, for which the broadest array of molecular and genetic tools are available.
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Clostridium clariflavum: Key Cellulosome Players Are Revealed by Proteomic Analysis

Clostridium clariflavum: Key Cellulosome Players Are Revealed by Proteomic Analysis

The separation of the cellulosome complexes from the spent growth medium by gel filtration resulted in an elution profile of two broad peaks, containing two discrete groups of cellulosome fractions. Mass spectrometry analysis showed that each peak con- tains cellulosomal proteins that differ in content and ratios of their component parts. The results allowed us to deduce the existence of several different types of cellulosome assemblies, shown in Fig. 3. The higher-molecular-mass first peak is mainly composed of two main complexes: (i) the ScaB adaptor scaffoldin, which carries five molecules of the primary scaffoldin ScaA, each of which bears eight enzymatic subunits, yielding a complex of 40 enzymatic sub- units (assuming full occupancy), and (ii) the cell-free ScaE, which carries seven ScaA molecules, resulting in complexes containing up to 56 enzymes (Fig. 3A). Considering the abundance of ScaB and ScaE in fraction I, the ScaB-based complex is the most abun- dant. In contrast, the second peak includes a different set of com- plex compositions of lower molecular mass: (i) the monovalent cell wall ScaF interacts with a single ScaA molecule and its eight enzymes; (ii) ScaM(b), a scaffoldin bearing six type I cohesins, interacts with six type I dockerins conjugated to a variety of en- zymes; and (iii) the single type I cohesin module of ScaG interacts with a type I dockerin of a cellulosomal enzyme (Fig. 3B). The variety of expressed cellulosomes discovered in this work reveal two complementary mechanisms of action employed by the bac- FIG 3 Major cellulosomes produced by C. clariflavum. Gel filtration separation of the spent growth medium resulted in two fractions which contain five major types of cellulosome complexes. (A) Two very large cellulosomes are present in fraction I. (i) Complex 1 is composed of five subunits of the octavalent ScaA, 40 enzymes, and the pentavalent ScaB. (ii) Complex II contains 7 subunits of ScaA, 56 enzymes, and the heptavalent ScaE. (B) Fraction II contains three cellulosomes. (i) Complex 1 contains a single ScaA subunit, 8 enzymes, and a monovalent ScaF. (ii) Complex 2 contains the hexavalent ScaM(b) subunit and 6 enzymes. (iii) Complex 3 contains ScaG, which binds a single enzyme via its type I cohesin module.
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Chemical analysis of multicellular tumour spheroids

Chemical analysis of multicellular tumour spheroids

characteristics. Oxygen concentration is singularly a measure- ment of the level of oxygen present while hypoxia is a more complex characteristic which can be defined in several ways including nitroreductase activity, 41 HIF activation 42 and expression of HIF associated genes 43 to name a few. This dis- tinction is important since a hypoxic phenotype (HIF stabilis- ation, glycolytic metabolism) is a characteristic of many cancers irrespective of oxygen concentration (Warburg E ff ect). 44 When considering chemical analysis of MTS some techniques have been developed specifically to measure hypoxia as a function of, for example, nitroreductase activity, while other techniques directly measure oxygen concentration. One of the first methods developed for measuring hypoxia uses small molecules such as 2-nitroimidazole that are meta- bolised under hypoxic conditions and subsequently detected. 45 An example is the commercially available Hypoxyprobe-1 ™ (PimonidazoleHCl) 46 , where the metabolised product in hypoxic regions is detected by an antibody and subsequently visualized by either a fluorescent tag 47 or colorimetric detec- tion (Fig. 5). This technique is limited to distinguishing cells below and above a hypoxic limit without giving truly quantitat- ive information. Autoradiography was used in initial detection methods for these probes and extension to magnetic reson- ance spectroscopy (MRS) and positron emission tomography (PET) allowed non-invasive detection of hypoxia in living systems. 48–54 Hypoxyprobe-1™ has been used to visualise dis- tributions of hypoxia in MTS, giving good spatial resolution, but its use is limited to fixed sections.
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Comparative proteomic analysis provides new insight into differential transmission of two begomoviruses by a whitefly

Comparative proteomic analysis provides new insight into differential transmission of two begomoviruses by a whitefly

According to the proteins of insects that have a complete genome, over 1% of the total proteins are cu- ticle proteins [49], indicating the importance of cuticle proteins in insect body. In our iTRAQ data, three cu- ticle proteins, cuticle protein 6 (1.26-fold), cuticle protein 67, isoform A (1.25-fold) and cuticle structural protein PCP16.7 (1.22-fold), were significantly up-regulated in the comparison of TYLCV-infected vs. un-infected white- flies, and two cuticle proteins, cuticle protein 21 (1.35-fold) and cuticle protein 7 (1.21-fold), were significantly up-regu- lated in the comparison of PaLCuCNV-infected vs. un-infected whiteflies. No cuticle proteins showed down- regulation in both comparisons. According to the analysis from CutProtFam, cuticle protein 6 and cuticle protein 21 belong to the CPR family and RR-2 subgroup, cuticle protein 67, isoform A belongs to CPF family. However, Table 1 DEPs involved in the pathway of ECM-receptor
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Tools to reverse-engineer multicellular systems: case studies using the fruit fly

Tools to reverse-engineer multicellular systems: case studies using the fruit fly

From the traditional fluorescence-based imaging to X-ray-based micro-CT, we are seeing a range of new im- aging technologies being applied to multicellular systems, including genetic model systems such as Drosophila. Advances in traditional fluorescence-based imaging is also significantly increasing image-acquisition speed, penetration and signal-to-noise ratio [93, 95, 96, 102]. In the meantime, label-free imaging of structure and/or measurements of tissue mechanics is leading to broader applications [111, 167]. These imaging modal- ities further combine with other technologies to provide increasing imaging capabilities. An emerging bottleneck for automating multimodal imaging experiments is the need to develop capabilities for parallel imaging modules integrated with customizable multichannel microfluidic devices to image many biological samples at a time. This, in turn, will increase the need for data storage and management solutions for labs. The significant advances being made in acquisition speed and resolution also de- mands a paradigm shift of analysis methods to handle the gigabytes and terabytes of data that are generated per imaging session [94, 96]. These new trends are blur- ring the knowledge boundaries of different research disciplines and encouraging the collaboration of micro- fluidic device designers, imaging technicians and com- puter vision scientists.
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Assessment of violations of the proteomic profile in blood plasma in children being under inhalation exposure to fine dust containing vanadium

Assessment of violations of the proteomic profile in blood plasma in children being under inhalation exposure to fine dust containing vanadium

tration in the blood of the exposed children aged 4- 7, which is 6,1-6,2 times higher than that in the blood of non-exposed children and the reference level. A correlation between the changes in the proteomic profile of the blood plasma and the con- centration of vanadium in it was confirmed. This is reflected in the changes at a molecular level in the form of a relatively increased alpha-acid glycopro- tein 1, reduced relative volume of clusterin, apolipoprotein A-IV, alpha-2-HS-glycoprotein. The lack of preventive measures can promote fur- ther functional disorders at the tissue and organ levels, and result in early osteoporosis and bone and joint disease, atherosclerotic vascular changes, autoimmune allergic processes along with immune disorders and cancer. The use of the identified pro- teins as markers of adverse effects in children ex- posed to the vanadium-containing emissions from the metallurgical plants is appropriate in terms of expanding the evidence of adverse health effects required for hygienic examinations and investiga- tions for an early detection and prevention of the risk of associated diseases.
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Proteomic analysis of albumins and globulins from wheat variety Chinese Spring and its fine deletion line 3BS-8

Proteomic analysis of albumins and globulins from wheat variety Chinese Spring and its fine deletion line 3BS-8

After electrophoresis, proteins were visualized by colloidal Coomassie Brilliant Blue (CBB) staining according to [26]. The 2-DE images were scanned by GS-800™ Calibrated Densitometer (BIO-RAD) and statistical analysis was performed by the ImageMaster 2D Platinum software (GE Healthcare) [27]. Determined by Student’s t test (abundance variation at least twofold, p < 0.05), protein spots of interest on the gels were selected for further analysis from those that showed statistically significant changes between samples.

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Host modulatory therapy : A treatment concept

Host modulatory therapy : A treatment concept

Periodontitis is defined as, ‘an inflammatory disease of the supporting tissues of the teeth caused by specific micro organisms or groups of specific micro-organisms, resulting in progressive destruction of the periodontal ligament and alveolar bone with pocket formation, recession, or both. Modulatory Therapy (HMT) is a treatment concept that aims to reduce tissue destruction and stabilize or even regenerate the periodontium by modifying or downregulating destructive aspects of the host response and upregulating
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Selective Proteomic Analysis of Antibiotic Tolerant Cellular Subpopulations in Pseudomonas aeruginosa Biofilms

Selective Proteomic Analysis of Antibiotic Tolerant Cellular Subpopulations in Pseudomonas aeruginosa Biofilms

An important recent advance has been the application of pulsed stable isotope labeling with amino acids in cell culture (pSILAC) to quantify changes in protein expression following adaptation of biofilm cells to challenge with antibiotics (15). Via pulsed addition of an amino acid isotopolog, pSILAC can provide a means to distin- guish, based on mass, proteins synthesized before and during the pulse (16). Chua et al. characterized the long-term proteomic response of tolerant cells by treating biofilms with the clinical polymyxin colistin for 8 h to allow nontolerant cells to die and then labeling newly synthesized proteins with an extended (48-h) amino acid isotopolog pulse. This approach ensured that labeled and identified proteins were synthesized over the 2-day period by the tolerant subpopulation of interest. The results of this study revealed the importance of type IV-mediated motility in the resistance of P. aeruginosa biofilms to colistin.
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Proteomic analysis of tears following acupuncture treatment for menopausal dry eye disease by two-dimensional nano-liquid chromatography coupled with tandem mass spectrometry

Proteomic analysis of tears following acupuncture treatment for menopausal dry eye disease by two-dimensional nano-liquid chromatography coupled with tandem mass spectrometry

Protein identification and quantification of iTRAQ data were performed using ProteinPilot software version 4.5 (AB SCIEX). The paragon algorithm in ProteinPilot software was used for peptide identification and isoform-specific quantifi- cation. The signal from the iTRAQ114 group served as the internal reference for signal intensity to which all signals were normalized. The weighted average of the ratios of the respective peptides was calculated based on the protein quan- titation results. False discovery rate analysis was conducted, and the detected protein threshold was set to ,0.01. The proteomic database used in this study was for Homo sapiens (UniProKB) (http://www.uniprot.org/uniprot).
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Non specific physiological background effects of acupuncture revealed by proteomic analysis in normal rats

Non specific physiological background effects of acupuncture revealed by proteomic analysis in normal rats

Many recent publications have explored the therapeutic effects of acupuncture, but surprisingly few insightful studies have dealt with the physiological background effects of acupuncture. Our previous study demonstrated that acupuncture had an immunomodulatory effect on inflammatory cells and cytokines that were associated with an improvement in general well-being [5,6]. We preliminarily analyzed the gene expression profile of acupuncture in normal rats using serial analyses of gene expression (SAGE) [7]. Experienced and effective acupuncture points, GV14 (Dazhui), BL12 (Fengmen) and BL13 (Feishu), were selected in the present study for acupuncture in normal rats, and a 2DE/MS-based proteomic analysis of the lung proteome was performed from acupuncture-treated normal rats to further elu- cidate the non-specific physiological background effects of acupuncture.
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Using quantitative proteomic analysis to understand genotype specific intrinsic drug resistance in melanoma

Using quantitative proteomic analysis to understand genotype specific intrinsic drug resistance in melanoma

When analyzing multiple fragments from different molecules, the technique is also called multiple reaction monitoring mass spectrometry (MRM-MS). The “reaction” is the conversion of the intact molecule into fragment ion(s) specific for its structure (see Figure 1A); this molecule-fragment pair is also termed a transition. Each “reaction” is optimized by the choice of background gas (typically argon or nitrogen) the pressure in the collision cell, and the collision energy applied. When coupled with reversed-phase liquid chromatography, three characteristics of the molecule are used to isolate its signal for detection and quantification: hydrophobicity (which defines the elution time), the mass-to-charge ratio (m/z) of the intact molecule, and fragment ion mass-to-charge ratio.
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Proteomic analysis of HIV 1 Gag interacting partners using proximity dependent biotinylation

Proteomic analysis of HIV 1 Gag interacting partners using proximity dependent biotinylation

subjected to ontology analysis using PANTHER (http:// www.pantherdb.org/) [5, 6]. In biological process, the most clusters identified were: metabolic process, cellular process and cellular component organization or biogenesis; whereas binding, catalytic activity and structural molecule activity dominated the clusters in molecular function (Fig. 2b). The protein classes related to nucleic acid binding were the most enriched with transferase, transfer/carrier protein and extracellular matrix protein exclusively found in BirA*-Gag (Fig. 2b). Physical and genetic interactions, pathways, and protein domain similarity between the genes linked with BirA*-Gag were mapped using GeneMANIA (http:// www.genemania.org) [7] (Fig. 2c). Compared to the
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Combined proteome and transcriptome analyses for the discovery of urinary biomarkers for urothelial carcinoma

Combined proteome and transcriptome analyses for the discovery of urinary biomarkers for urothelial carcinoma

Despite intensive efforts to discover useful biomarkers for the non- invasive detection of cancer using increasingly powerful ‘omic’ technologies there is still a dearth of diagnostic markers available (Anderson, 2010). If such markers do actually exist they have evaded discovery due to their low concentration in very complex backgrounds. The methodological difficulties such samples present, particularly in proteomic work, should not be underestimated (Ray et al, 2011). A recently adopted approach has been to compare proteomic analysis of proteins secreted from cancer-specific cell lines to changes in gene expression in cancer tissue from the same cancer type (Chang et al, 2010, 2011; Wang et al, 2011; Yu et al,
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Direct effects of physical training on markers of bone metabolism and serum sclerostin concentrations in older adults with low bone mass

Direct effects of physical training on markers of bone metabolism and serum sclerostin concentrations in older adults with low bone mass

The anabolic effect of physical exercise on osseous tissue is related to mechanical effort, although the osteogenic re- sponse may also be influenced by other factors [3]. Physical loads associated with exercise impact bone mass and struc- ture by causing dynamic changes to local mechanical con- ditions, which stimulate resident osteocytes through fluid shifts in their canalicular network. These osteocytes then produce signaling molecules that regulate bone formation and absorption by osteoblast and osteoclasts [4]. Bone tissue has an intrinsic “mechanostat” that regulates func- tional adaptation to stresses [5]. Bone deformation of 1500–3000 με (physiological overload) induces modeling of the bone cortex, while that of 100–300 με induces bone multicellular unit (BMU) remodeling. Strain below 100 με
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<p>Integrated Datasets of Proteomic and Metabolomic Biomarkers to Predict Its Impacts on Comorbidities of Type 2 Diabetes Mellitus</p>

<p>Integrated Datasets of Proteomic and Metabolomic Biomarkers to Predict Its Impacts on Comorbidities of Type 2 Diabetes Mellitus</p>

In the current study, IPA software was used to integrate the fold expression of DRGs for the development of molecular pathways and networks in T2DM. As illustrated in this study, the data explore signi fi cant pathways in T2DM subjects com- pared to control subjects to gain more understandings of the pathogenesis towards diabetic complications. This study iden- ti fi ed differentially dysregulated genes as potential prognostic biomarkers involved in critical biological processes and path- ways of proteins that are allied with T2DM comorbidities. The most important fi ndings of this study are the identi fi cation of the upstream regulators which affect the gene expression such as transcription factors STAT3, STAT1, and HIF1A, cytoplas- mic kinases such as JAK kinases and highlight their mechan- istic actions that affect the expression. Furthermore, the fi ndings of the present study identi fi ed the most commonly expressed genes: Tumor Necrosis Factor, TNF, Interleukin 6; IL6, Leptin; LEP, Angiotensinogen; AGT, Apolipoprotein E; APOE,Coagulation Factor II, Thrombin; F2, Secreted Phosphoprotein 1; SPP1,Resistin; RETN, and Insulin; INS that could be used as potential prognostic biomarkers. The data recognized that IL6 is the top regulator of the DRGs, followed by LEP. The study identi fi ed several networks which explore the dysregulation of several functions, including Table 9 Top Five Upstream Kinase Factors Affecting the Expression of the Genes of the Data Set of the Present Study with their p- values, Z-Score, Target Molecule and Numbers of Mechanistic Works. (Based on Core Analysis in Ingenuity Pathway Analysis [IPA])
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A survey of computational tools for downstream analysis of proteomic and other omic datasets

A survey of computational tools for downstream analysis of proteomic and other omic datasets

Machine learning and its methods have increasingly gained attention in bioinformatics research. With the availability of different types of classification methods, it is common for researchers to apply these tools to clas- sify and mine their data. But one should keep in mind that no matter how sophisticated the bioinformatics tools, the quality of the results they produce is directly dependent on the quality of input data they are given. In addition, new experimental methods are likely to require newly adapted bioinformatics tools as mass spectrome- ters become more powerful and as novel experimental design results in more complex datasets. One area of rapidly expanding complexity is at the integration of the fronts of metabolomic and proteomic data. Each soft- ware tool has some advantage and disadvantage, so it benefits the user to employ a combination of tools to examine one dataset rather than a single software tool. Each dataset contains its own quirks, positive and nega- tive, and it is up to the end users and analysts to decide the most effective approach for assessing the biology that is taking place within their experiment.
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