Find the odd man out respect to chemoautotrophs
To save this word, you'll need to log in. Log In Definition of odd man out : a person who differs from the other members of a group Examples of odd man out in a Sentence Recent Examples on the Web Michigan State seems destined for New York, and several projections have Eastern Michigan as the odd man out for bowl season there are 79 bowl-eligible teams for 78 slots. Lille in Champions League," 2 Oct. He Wants to Go. Send us feedback.SEE VIDEO BY TOPIC: Odd Man Out Series - Find the Odd Number from the Random Series
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- Bacteria, Bacteriophages, and Fungi
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- Reasoning - Odd Man Out
- Scientists discover evidence of ancient, nitrogen-rich Martian groundwater hiding in Antarctica
- ICSE Solutions for Class 10 Biology – Photosynthesis
- CLS Aipmt 17 18 XIII Zoo Study Package 4 SET 1 Chapter 14
odd man out
Insight into the transcription-regulatory network that coordinates these processes is fundamental to understanding the biology of this versatile bacterium. With this goal in mind, we predicted regulatory signals genomewide, using a two-step phylogenetic-footprinting and clustering process that we had developed previously.
In the first step, 4, putative transcription factor binding sites, upstream of 2, genes and operons, were identified using cross-species Gibbs sampling. Bayesian motif clustering was then employed to group the cross-species motifs into regulons.
We have identified putative regulons in R. In some cases, clustering allowed us to assign functions to proteins that previously had been annotated with only putative functions; we have identified RPA as the organic hydroperoxide resistance regulator and RPA as a cell cycle methylase.
In addition to predicting regulons, we identified a novel inverted repeat that likely forms a highly conserved stem-loop and that occurs downstream of over genes.
These metabolically adaptable species are found in a variety of niches, including marine environments, freshwater sediments, and soil, and they have the ability to photosynthesize, fix carbon dioxide, and fix nitrogen.
Plant-associated species include Bradyrhizobium japonicum , a soybean symbiote, and Agrobacterium tumefaciens , the causative agent of crown gall disease. Animal pathogens include Bartonella henselae , Rickettsia prowazekii , and Brucella suis , the causative agents of cat scratch disease, typhus fever, and porcine brucellosis, respectively.
The purple photosynthetic bacterium R. In addition to its ability to photosynthesize, fix carbon dioxide, and fix nitrogen, R.
Under anaerobic conditions in the presence of light, the bacterium forms stacked membrane structures that house the photosynthetic machinery and generate energy It can produce hydrogen using a nitrogenase-dependent mechanism, thus making it a potential bioenergy source 2. The R. It has been suggested that the immobilized cells may be exploited in the fabrication of biocatalysts The potential applications in energy production, bioremediation, and biocatalysis make R.
In order to realize that potential, it is important that we first understand the regulation of R. A consequence of R. Cellular processes, such as nitrogen fixation and carbon dioxide fixation, are energy intensive; thus, the enzymes for these pathways must be regulated with respect to nutrient availability and other environmental factors for reviews, see references 7 , 8 , and For example, it is most efficient for the bacterium to regulate the synthesis of its photosynthetic machinery with respect to light intensity and wavelength The presence of a sophisticated regulatory network is supported by the large number of annotated transcription-regulatory and signaling proteins genes encoded in the R.
The first goal of this study was to identify transcription factor binding sites TFBSs genomewide by phylogenetic footprinting. Phylogenetic footprinting is an approach to discover regulatory motifs in orthologous intergenic regions. The assumption is that among a phylogenetically close group of species, orthologous genes are likely to be regulated by a common transcription factor TF.
Under this assumption, the TFBSs will be conserved, while other noncoding DNA that is not under selective pressure will be free to mutate over time. Thus, the promoter regions upstream of orthologous genes are analyzed for putative regulatory motifs by computationally searching for conserved sequence elements. In the current study, conserved sequences were found using a Gibbs sampling strategy. This approach predicts regulatory motifs de novo without any prior knowledge regarding binding sites and exploits the diversity of the contributing species in order to increase the power of the search for regulatory motifs.
An advantage of using the Gibbs sampler for these studies is that it implements a rigorous Bayesian method to infer the number of sites and their locations Accordingly, a TFBS that is present in an intergenic region of the target species and some of the species in the collection may be absent in others. This feature is important, since the selection of species for phylogenetic footprinting is empirical; we require only that the species be phylogenetically related so that they have a significant number of common TFs Furthermore, among the remaining novel predictions were TFBSs predicted upstream of fatty acid biosynthesis genes; these sites were used to affinity purify a previously uncharacterized TF YijC that has since been shown to regulate fatty acid biosynthesis in vivo The second goal of this study was to cluster these predicted cis regulatory elements into regulons.
Clustering provides a mechanism by which motifs that represent binding sites for the same TF are grouped; this combined evidence improves the reliability of pathway and cognate TF identification. We used a Bayesian clustering algorithm developed previously that was found to accurately cluster Escherichia coli regulatory motifs A total of putative R. Orthologous intergenic regions were identified as previously described Upstream orthologous intergenic regions were extracted from the database with a maximum length of bp and a minimum length of 50 bp.
In some cases, it was obvious that the start codons for genes in R. In cases, we identified a more likely downstream start codon. Potential artifacts arising from the shifting of these start codons were minimized by tracking the revised genes throughout the phylogenetic-footprinting and clustering process.
The recursive Gibbs sampler Gibbs v 2. A Bayesian segmentation algorithm was used to generate a position-specific background composition model for each sequence in a data set Unifiedcpp All models consisted of 16 active columns that were allowed to fragment to a maximum width of 24 columns. For the detection of palindromes, the Gibbs sampler was allowed to choose an even- or odd-width palindromic model, based on the sequence evidence.
The sampler was allowed to run for 2, iterations, with a plateau period of iterations, and it was reinitialized 40 times using random seeds. This average MAP cutoff was chosen empirically. The entire process sampling and masking was repeated three times to take advantage of the stochastic nature of Gibbs sampling and to maximize the number of motifs found.
Motifs that contained unique sites in R. We selected motifs for clustering by first applying a critical-value criterion; palindromic and nonpalindromic motifs were compared to model-specific critical-value criteria derived from random data simulations Coding sequence contamination in the extracted intergenic regions was detected through comparison of the coordinates of each site in a motif to the available genome annotations R.
If more than half of the sites from annotated species overlapped a coding region, the motif was eliminated from clustering. Motifs were also analyzed for the presence of shared sites. If two motifs contained the same site from more than one species, or if motifs contained the same site from R.
Clustering was carried out using the Bayesian motif clustering algorithm BMC v 1. Even-, odd-, and nonpalindromic models were clustered separately using a tuning parameter q of This parameter, which affects whether a motif forms a cluster on its own or whether the motif joins an existing cluster, was determined empirically. BMC was run for 10 iterations without fragmentation, followed by 25 iterations with the fragmentation option enabled, to produce the optimal solution.
BMC was then allowed to sample for an additional iterations to produce the frequency solution described in this study. All clusters were initially allowed to shift, meaning that motifs could realign with respect to each other within a cluster.
The shifting option did not influence the alignment of motifs in palindromic clusters and was turned off. Shifting did, however, improve the alignment of nonpalindromic motifs within a cluster; thus, we allowed nonpalindromic motifs to shift left or right by up to two columns.
Cluster models from the frequency solution were used as input to the Dscan algorithm Dscan revision 2. The complete set of R. Given the input model and database, Dscan uses the approach described by Staden 44 to report sites that match the model above a given level of statistical significance.
The choice of species to be used for phylogenetic footprinting was governed by two factors: their phylogenetic relatedness and the presence of common metabolic pathways. Current alignment algorithms, including Gibbs sampling, do not account for the phylogenetic relatedness correlation of the input data, which leads to overestimation of the significance of motifs. Therefore, to achieve sufficient phylogenetic diversity and minimize losses to the power of the cross-species technique due to phylogenetic correlations among the sequence data, we chose R.
This means that, although additional genome sequences were available, they were not expected to improve the reliability of predictions in R. This is why, for instance, only one of the sequenced Brucella species was retained. Six of the eight species shown in Fig.
The conservation of TFs across species was examined, and of the R. Using the set of eight species, we compiled orthologous upstream intergenic sequence data sets representing 2, R. A total of 4, motifs were found for 2, of these data sets by phylogenetic footprinting. Statistical-significance criteria were determined using a random data simulation as described by McCue and coworkers A BMC algorithm 38 was used to infer regulons from the collection of motifs found by phylogenetic footprinting.
After applying filtering heuristics see Materials and Methods to the 2, motifs described above, we identified 1, motifs for clustering. However, we have found that the noise introduced into the clustering procedure by false-positive motif predictions has little effect on true regulons; specifically, the false-positive motif predictions do not join clusters reproducibly L.
McCue, unpublished data. This is supported by the observation that only of the input motifs reproducibly joined a cluster and are reported as members of regulons. Furthermore, we calculate a Bayes ratio as a measure of cluster strength and have found true regulons to rank among the highest scoring. The Bayes ratio is the ratio of the probability of the data belonging in a cluster to the probability of the data existing as separate motifs. The clusters represent partial regulons, including only those regulatory sites that could be detected by our cross-species approach.
For example, R. It is also the case that the heuristics used to filter out motifs prior to clustering may eliminate some legitimate motifs. One way in which to address this problem is to scan the complete set of intergenic regions for a species, using position weight matrices built from the clusters.
This approach often results in the prediction of additional members of a regulon We employed a rigorous statistical algorithm based on Staden's method 44 as implemented by Neuwald and coworkers 34 to scan for additional TFBSs in R. The algorithm yields a P value for a motif match that represents the probability that a site of equal or greater strength would be found in a random data set of the same size and composition. In scans of the set of all intergenic regions of R.
Phylogenetic footprinting, clustering, and scanning are summarized in Fig. Flowchart of phylogenetic footprinting, clustering, and scanning. The phylogenetic-footprinting procedure is shown above the dashed line, and the clustering procedure is shown below.
Input data and intermediate data sets are shown in boxes. Operations are shown in rounded boxes.
Bacteria, Bacteriophages, and Fungi
Green  and stars James Mason and Robert Newton. It followed upon wartime action by the IRA in Belfast, in consequence of which Northern Ireland undertook its first and only execution of an Irish Republican , year old Tom Williams. The film's opening intertitle reads: "This story is told against a background of political unrest in a city of Northern Ireland. It is not concerned with the struggle between the law and an illegal organisation, but only with the conflict in the hearts of the people when they become unexpectedly involved. The city and the organisation are never explicitly named.
Aptitude - Odd Man Out and Series
Question 1: What are the basic requirements of photosynthesis? Answer: The basic requirements of photosynthesis are:. Question 2: i Where are the chlorophyll pigments present in a cell. Answer: i In the cell organelle called plastids or chloroplasts. Question 3: Give some adaptations in a green leaf for photosynthesis. Answer: i A large surface area to absorb water. Question 4: What is the importance of photosynthesis in the life of the following : i Green plants ii Non-green plants iii Animals Answer: i Green plants are able to build up complex energy rich molecules of carbohydrates which are further used for different metabolic activities of cells. Question 5: A leaf is a food factory. Answer: The leaves of green plants are specially developed for the purpose of synthesizing food.
Odd Man Out
Origin of earth dates back to 1 10,—15, million years ago 2 — million years ago 3 — million years ago 4 — million years ago Sol. Who finally refuted the theory of spontaneous generation and experimentally disproved it? Answer 3 Louis Pasteur disproved it by Swan neck experiment. An experiment to prove that organic compounds were the basis of life, was performed by 1 Van Helmont 2 Oparin 3 S.
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In every competitive exam, Odd Man Out type questions are very common. In odd man out problems all the items given in the question except one follow a certain pattern or a group. That means out of the all given elements, one will not fall into the group due to some difference in the property. That is the odd element. Hence, it is the odd one.
Reasoning - Odd Man Out
A bit of 4-billion-year-old rock blasted off the Martian surface about 15 million years ago and eventually landed in Antarctica , where explorers found it in In the decades since, organic compounds found in that meteorite have been sources of controversy: Did they come from Mars, or did the meteorites get contaminated on Earth? Now, a team of Japanese researchers has reexamined the meteorites, and say they found traces of ancient oceans, rich in useful carbon and nitrogen — key ingredients for life. The meteorite, known as Allan Hills , after the location where it was first discovered, has long been known to contain organic materials. The hunk of space rock has been the subject of paper after paper after paper debating whether those materials came from Earth or Mars.
Scientists discover evidence of ancient, nitrogen-rich Martian groundwater hiding in Antarctica
ICSE Solutions for Class 10 Biology – Photosynthesis
CLS Aipmt 17 18 XIII Zoo Study Package 4 SET 1 Chapter 14