() First strand cDNA is initiated by priming with an oligo dT primer containing and anchoring primer site

<p><b>Copyright information:</b></p><p>Taken from "Options available for profiling small samples: a review of sample amplification technology when combined with microarray profiling"</p><p>Nucleic Acids Research 2006;34(3):996-1014.</p><p>Published online 9 Feb 2006</p><p>PMCID:PMC1363777.</p><p>© The Author 2006. Published by Oxford University Press. All rights reserved</p> The template switch effect is applied to incorporate a primer containing both an anchoring primer site and a RNA polymerase binding site. The anchored priming sites are used in a limited PCR cycling step. Sense RNA (sRNA) is transcribed by SP6-RNA polymerase during an reaction. Adapted figure from Rajeevan . (). () The first round of this procedure is equivalent to the first round of the classical Eberwine procedure and RNA in the antisense direction is synthesized in the reaction. At the start of the second round of amplification, aRNA is primed with random nonamer primers modified by the addition of an upstream T3 polymerase promoter site. Second strand cDNA is synthesized as in the Eberwine protocol. The RNA transcripts produced in this second amplification round are oriented in the sense direction. Modified figure from Kaposi-Novak . (). ( and ). An oligo dT primer and a terminal continuation (TC) primer containing a T7 promoter sequence in the sense oriented transcription are added to the mRNA sample for first strand cDNA synthesis. TC is based on the observation of the reverse transcriptase enzyme adds a few Cs and also Gs nonspecifically at the end of mRNA templates. The TC primer anneals with this stretch and provides a binding site for second strand cDNA synthesis. RNA transcription can be driven using a promoter sequence attached to either the 3′ or the 5′ oligo primers and in thus generates either sense or antisense RNA transcripts. For further methodological details of the terminal continuation strategy see Che and Ginsberg (). () The first and subsequent rounds of amplification follow the same procedure as the classical Eberwine method. The final aRNA is reverse transcribed into sense cDNA and used as a template for Klenow labeling, yielding fluorescently labeled antisense cDNA, which are in the correct orientation for hybridization to oligo arrays. Adapted figure from Schlingemann . ()

Overview of a linear mRNA amplification based on the procedure described by Wang

<p><b>Copyright information:</b></p><p>Taken from "Options available for profiling small samples: a review of sample amplification technology when combined with microarray profiling"</p><p>Nucleic Acids Research 2006;34(3):996-1014.</p><p>Published online 9 Feb 2006</p><p>PMCID:PMC1363777.</p><p>© The Author 2006. Published by Oxford University Press. All rights reserved</p> (). Following oligo dT priming, the method exploits the template switching effect of the reverse transcriptase enzyme. The RT enzyme incorporates non-template dCTPs at the 3′ end of the transcript, then switches templates and continues replication to the end of the primer. The result is full length cDNA. For the second strand, a primer with bases complementary to the dCTP stretch is applied. Antisense RNA is transcribed by the T7 RNA polymerase

Additional file 3: Table S3. of Profiling networks of distinct immune-cells in tumors

The resultant general immune-cell type (GIT) and DIST marker genes identified using the bioinformatics workflow. (XLS 85 kb

Additional file 2: Table S2. of Profiling networks of distinct immune-cells in tumors

List of DISTs with significant differences (logrank p values) in the Kaplan Meier curves between groups in highest and lowest quartile for the DIST, in a metastatic melanoma cohort of patients who have undergone chemotherapy. (XLS 30 kb

Additional file 4: Table S4. of Profiling networks of distinct immune-cells in tumors

List of DISTs ratios with significant differences (logrank p values) in the Kaplan Meier curves between groups in highest and lowest quartile for the DIST ratio, in the metastatic melanoma cohort of patients. (XLS 215 kb

Additional file 1: Additional Tables S1 and S2. of Genome build information is an essential part of genomic track files

(PDF 79 kb

Understanding the Melanocyte Distribution in Human Epidermis: An Agent-Based Computational Model Approach

<div><p>The strikingly even color of human skin is maintained by the uniform distribution of melanocytes among keratinocytes in the basal layer of the human epidermis. In this work, we investigated three possible hypotheses on the mechanism by which the melanocytes and keratinocytes organize themselves to generate this pattern. We let the melanocyte migration be aided by (1) negative chemotaxis due to a substance produced by the melanocytes themselves, or (2) positive chemotaxis due to a substance produced by keratinocytes lacking direct physical contact with a melanocyte, or (3) positive chemotaxis due to a substance produced by keratinocytes in a distance-to-melanocytes dependent manner. The three hypotheses were implemented in an agent-based computational model of cellular interactions in the basal layer of the human epidermis. We found that they generate mutually exclusive predictions that can be tested by existing experimental protocols. This model forms a basis for further understanding of the communication between melanocytes and other skin cells in skin homeostasis.</p></div

Melanocyte uniformity measurements.

<p>As quantitative measurements of the three different mechanisms’ ability to distribute melanocytes evenly, we counted the number of melanocytes with three or more melanocyte neighbors (top), and the relative standard deviation of the distance from all melanocytes to the nearest other melanocyte (bottom). All measurements are given as mean and standard deviation of 12 repetitions. A Kolmogorov–Smirnov test was performed to test for significant differences between the hypotheses at each parameter setting of which the results are given in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0040377#pone-0040377-t001" target="_blank"><b>Table 1</b></a>.</p

Scripts and URLs used in database queries and web-crawling for article "Genome build information is an essential part of genomic track files"

<p>All the scripts used for web crawling, querying the databases, retrieving the files and all URLs of the files retrieved for the article "Genome build information is an essential part of genomic track files".</p

Signal gradient as produced by our diffusion model.

<p>Two different views of three different virtual cell cultures are shown. In the left panels the cells are colored according to cell type; keratinocytes blue and melanocytes red, while in the right panels cells are colored according to strength of signal (lighter color equals higher concentration). The signal substance diffuses from cell to cell and degrades according to our diffusion model. In these simulations, we have restricted the melanocytes to reside at the outer rim of the dish in order to visualize the global gradient towards the middle. In A, the cells are colored according to the concentration of signal substance R that is produced by all melanocytes at a constant rate. In B and C, the cells are colored according to the concentration of the attracting signal substance A. The gradient in B is generated by production of signal in all keratinocytes not in contact with a melanocyte (A, binary), while in C the gradient is set up by production of signal in all keratinocytes as a function of the strength of the signal R (A, R-dependent).</p