| 1. |
- Thomas, HS, et al.
(författare)
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- 2019
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swepub:Mat__t
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| 2. |
- Birney, Ewan, et al.
(författare)
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Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project
- 2007
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 447:7146, s. 799-816
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Tidskriftsartikel (refereegranskat)abstract
- We report the generation and analysis of functional data from multiple, diverse experiments performed on a targeted 1% of the human genome as part of the pilot phase of the ENCODE Project. These data have been further integrated and augmented by a number of evolutionary and computational analyses. Together, our results advance the collective knowledge about human genome function in several major areas. First, our studies provide convincing evidence that the genome is pervasively transcribed, such that the majority of its bases can be found in primary transcripts, including non-protein-coding transcripts, and those that extensively overlap one another. Second, systematic examination of transcriptional regulation has yielded new understanding about transcription start sites, including their relationship to specific regulatory sequences and features of chromatin accessibility and histone modification. Third, a more sophisticated view of chromatin structure has emerged, including its inter-relationship with DNA replication and transcriptional regulation. Finally, integration of these new sources of information, in particular with respect to mammalian evolution based on inter- and intra-species sequence comparisons, has yielded new mechanistic and evolutionary insights concerning the functional landscape of the human genome. Together, these studies are defining a path for pursuit of a more comprehensive characterization of human genome function.
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| 3. |
- Bertone, Paul, et al.
(författare)
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Design optimization methods for genomic DNA tiling arrays.
- 2006
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Ingår i: Genome Research. - : Cold Spring Harbor Laboratory. - 1088-9051 .- 1549-5469. ; 16:2, s. 271-281
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Tidskriftsartikel (refereegranskat)abstract
- A recent development in microarray research entails the unbiased coverage, or tiling, of genomic DNA for the large-scale identification of transcribed sequences and regulatory elements. A central issue in designing tiling arrays is that of arriving at a single-copy tile path, as significant sequence cross-hybridization can result from the presence of non-unique probes on the array. Due to the fragmentation of genomic DNA caused by the widespread distribution of repetitive elements, the problem of obtaining adequate sequence coverage increases with the sizes of subsequence tiles that are to be included in the design. This becomes increasingly problematic when considering complex eukaryotic genomes that contain many thousands of interspersed repeats. The general problem of sequence tiling can be framed as finding an optimal partitioning of non-repetitive subsequences over a prescribed range of tile sizes, on a DNA sequence comprising repetitive and non-repetitive regions. Exact solutions to the tiling problem become computationally infeasible when applied to large genomes, but successive optimizations are developed that allow their practical implementation. These include an efficient method for determining the degree of similarity of many oligonucleotide sequences over large genomes, and two algorithms for finding an optimal tile path composed of longer sequence tiles. The first algorithm, a dynamic programming approach, finds an optimal tiling in linear time and space; the second applies a heuristic search to reduce the space complexity to a constant requirement. A Web resource has also been developed, accessible at http://tiling.gersteinlab.org, to generate optimal tile paths from user-provided DNA sequences.
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| 4. |
- Czeszumski, Artur, et al.
(författare)
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#EEGManyLabs: Investigating the Replicability of Influential EEG Experiments
- 2024
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- There is growing awareness across the neuroscience community that the replicability of findings on the relationship between brain activity and cognitive phenomena can be improved by conducting studies with high statistical power that adhere to well-defined and standardized analysis pipelines. Inspired by efforts from the psychological sciences, and with the desire to examine some of the foundational findings using electroencephalography (EEG), we have launched #EEGManyLabs, a large-scale international collaborative replication effort. Since its discovery in the early 20th century, EEG has had a profound influence on our understanding of human cognition, but there is limited evidence on the replicability of some of the most highly cited discoveries. After a systematic search and selection process, we have identified 27 of the most influential and continually cited studies in the field. We plan to directly test the replicability of key findings from 20 of these studies in teams of at least three independent laboratories. The design and protocol of each replication effort will be submitted as a Registered Report and peer-reviewed prior to data collection. Prediction markets, open to all EEG researchers, will be used as a forecasting tool to examine which findings the community expects to replicate. This project will update our confidence in some of the most influential EEG findings and generate a large open access database that can be used to inform future research practices. Finally, through this international effort, we hope to create a cultural shift towards inclusive, high-powered multi-laboratory collaborations.
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| 5. |
- Emanuelsson, Olof, et al.
(författare)
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Assessing the performance of different high-density tiling microarray strategies for mapping transcribed regions of the human genome.
- 2007
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Ingår i: Genome Research. - : Cold Spring Harbor Laboratory. - 1088-9051 .- 1549-5469. ; 17:6, s. 886-897
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Tidskriftsartikel (refereegranskat)abstract
- Genomic tiling microarrays have become a popular tool for interrogating the transcriptional activity of large regions of the genome in an unbiased fashion. There are several key parameters associated with each tiling experiment (e.g., experimental protocols and genomic tiling density). Here, we assess the role of these parameters as they are manifest in different tiling-array platforms used for transcription mapping. First, we analyze how a number of published tiling-array experiments agree with established gene annotation on human chromosome 22. We observe that the transcription detected from high-density arrays correlates substantially better with annotation than that from other array types. Next, we analyze the transcription-mapping performance of the two main high-density oligonucleotide array platforms in the ENCODE regions of the human genome. We hybridize identical biological samples and develop several ways of scoring the arrays and segmenting the genome into transcribed and nontranscribed regions, with the aim of making the platforms most comparable to each other. Finally, we develop a platform comparison approach based on agreement with known annotation. Overall, we find that the performance improves with more data points per locus, coupled with statistical scoring approaches that properly take advantage of this, where this larger number of data points arises from higher genomic tiling density and the use of replicate arrays and mismatches. While we do find significant differences in the performance of the two high-density platforms, we also find that they complement each other to some extent. Finally, our experiments reveal a significant amount of novel transcription outside of known genes, and an appreciable sample of this was validated by independent experiments.
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| 6. |
- Euskirchen, Ghia M, et al.
(författare)
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Mapping of transcription factor binding regions in mammalian cells by ChIP : comparison of array- and sequencing-based technologies.
- 2007
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Ingår i: Genome Research. - : Cold Spring Harbor Laboratory. - 1088-9051 .- 1549-5469. ; 17:6, s. 898-909
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Tidskriftsartikel (refereegranskat)abstract
- Recent progress in mapping transcription factor (TF) binding regions can largely be credited to chromatin immunoprecipitation (ChIP) technologies. We compared strategies for mapping TF binding regions in mammalian cells using two different ChIP schemes: ChIP with DNA microarray analysis (ChIP-chip) and ChIP with DNA sequencing (ChIP-PET). We first investigated parameters central to obtaining robust ChIP-chip data sets by analyzing STAT1 targets in the ENCODE regions of the human genome, and then compared ChIP-chip to ChIP-PET. We devised methods for scoring and comparing results among various tiling arrays and examined parameters such as DNA microarray format, oligonucleotide length, hybridization conditions, and the use of competitor Cot-1 DNA. The best performance was achieved with high-density oligonucleotide arrays, oligonucleotides >/=50 bases (b), the presence of competitor Cot-1 DNA and hybridizations conducted in microfluidics stations. When target identification was evaluated as a function of array number, 80%-86% of targets were identified with three or more arrays. Comparison of ChIP-chip with ChIP-PET revealed strong agreement for the highest ranked targets with less overlap for the low ranked targets. With advantages and disadvantages unique to each approach, we found that ChIP-chip and ChIP-PET are frequently complementary in their relative abilities to detect STAT1 targets for the lower ranked targets; each method detected validated targets that were missed by the other method. The most comprehensive list of STAT1 binding regions is obtained by merging results from ChIP-chip and ChIP-sequencing. Overall, this study provides information for robust identification, scoring, and validation of TF targets using ChIP-based technologies.
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| 7. |
- Gerstein, Mark B, et al.
(författare)
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What is a gene, post-ENCODE? : History and updated definition
- 2007
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Ingår i: Genome Research. - : Cold Spring Harbor Laboratory. - 1088-9051 .- 1549-5469. ; 17:6, s. 669-681
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Tidskriftsartikel (refereegranskat)abstract
- While sequencing of the human genome surprised us with how many protein-coding genes there are, it did not fundamentally change our perspective on what a gene is. In contrast, the complex patterns of dispersed regulation and pervasive transcription uncovered by the ENCODE project, together with non-genic conservation and the abundance of noncoding RNA genes, have challenged the notion of the gene. To illustrate this, we review the evolution of operational definitions of a gene over the past century--from the abstract elements of heredity of Mendel and Morgan to the present-day ORFs enumerated in the sequence databanks. We then summarize the current ENCODE findings and provide a computational metaphor for the complexity. Finally, we propose a tentative update to the definition of a gene: A gene is a union of genomic sequences encoding a coherent set of potentially overlapping functional products. Our definition side-steps the complexities of regulation and transcription by removing the former altogether from the definition and arguing that final, functional gene products (rather than intermediate transcripts) should be used to group together entities associated with a single gene. It also manifests how integral the concept of biological function is in defining genes.
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| 8. |
- Royce, Thomas E., et al.
(författare)
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Extrapolating traditional DNA microarray statistics to tiling and protein microarray technologies
- 2006
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Ingår i: Methods in Enzymology. - 0076-6879 .- 1557-7988. ; 411, s. 282-311
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Tidskriftsartikel (refereegranskat)abstract
- A credit to microarray technology is its broad application. Two experiments--the tiling microarray experiment and the protein microarray experiment--are exemplars of the versatility of the microarrays. With the technology's expanding list of uses, the corresponding bioinformatics must evolve in step. There currently exists a rich literature developing statistical techniques for analyzing traditional gene-centric DNA microarrays, so the first challenge in analyzing the advanced technologies is to identify which of the existing statistical protocols are relevant and where and when revised methods are needed. A second challenge is making these often very technical ideas accessible to the broader microarray community. The aim of this chapter is to present some of the most widely used statistical techniques for normalizing and scoring traditional microarray data and indicate their potential utility for analyzing the newer protein and tiling microarray experiments. In so doing, we will assume little or no prior training in statistics of the reader. Areas covered include background correction, intensity normalization, spatial normalization, and the testing of statistical significance.
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| 9. |
- Snyder, Joel S., et al.
(författare)
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#EEGManyLabs: Investigating the replicability of influential EEG experiments
- 2021
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Ingår i: Cortex. - : Elsevier. - 1973-8102 .- 0010-9452. ; 144, s. 213-229
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Tidskriftsartikel (refereegranskat)abstract
- There is growing awareness across the neuroscience community that the replicability of findings about the relationship between brain activity and cognitive phenomena can be improved by conducting studies with high statistical power that adhere to well-defined and standardised analysis pipelines. Inspired by recent efforts from the psychological sciences, and with the desire to examine some of the foundational findings using electroencephalog-raphy (EEG), we have launched #EEGManyLabs, a large-scale international collaborative replication effort. Since its discovery in the early 20th century, EEG has had a profound in-fluence on our understanding of human cognition, but there is limited evidence on the replicability of some of the most highly cited discoveries. After a systematic search and se-lection process, we have identified 27 of the most influential and continually cited studies in the field. We plan to directly test the replicability of key findings from 20 of these studies in teams of at least three independent laboratories. The design and protocol of each replication effort will be submitted as a Registered Report and peer-reviewed prior to data collection. Prediction markets, open to all EEG researchers, will be used as a forecasting tool to examine which findings the community expects to replicate. This project will update our confidence in some of the most influential EEG findings and generate a large open access database that can be used to inform future research practices. Finally, through this international effort, we hope to create a cultural shift towards inclusive, high-powered multi-laboratory collaborations. (c) 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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