Search
- Filter Results
- Location
- Classification
- Include attachments
- https://bio.libretexts.org/Bookshelves/Computational_Biology/Book%3A_Computational_Biology_-_Genomes_Networks_and_Evolution_(Kellis_et_al.)/05%3A_Genome_Assembly_and_Whole-Genome_Alignment/5.07%3A_Whole_Genome_DuplicationAs you trace species further back in evolutionary time, you have the ability to ask different sets of questions. Looking at the dotplot of S.cerevisiae chromosomes and K.waltii scaffolds, a divergence...As you trace species further back in evolutionary time, you have the ability to ask different sets of questions. Looking at the dotplot of S.cerevisiae chromosomes and K.waltii scaffolds, a divergence was noted along the diagonal in the middle of the plot, whereas most pairs of conserved region exhibit a dot plot with a clear and straight diagonal. Viewing the segment at a higher magnification (Figure 5.25), it seems that S.cerevisiae sister fragments all map to corresponding K.waltii scaffolds.
- https://bio.libretexts.org/Bookshelves/Computational_Biology/Book%3A_Computational_Biology_-_Genomes_Networks_and_Evolution_(Kellis_et_al.)/09%3A_Gene_Identification-_Gene_Structure_Semi-Markov_CRFS/9.07%3A_Other_MethodsBesides HMMs and CRFs, other methods do exist for computational gene identification. Semi-markov models generate variable sequence length emissions, meaning that the transitions are not entirely memor...Besides HMMs and CRFs, other methods do exist for computational gene identification. Semi-markov models generate variable sequence length emissions, meaning that the transitions are not entirely memory-less on the hidden states. These methods have not yet been applied to mammalian genomes. 4 For better understanding of SVM: http://dspace.mit.edu/bitstream/hand...663/6-034Fall- 2002/OcwWeb/Electrical-Engineering-and-Computer-Science/6-034Artificial-IntelligenceFall2002/Tools/detail/svmachine.htm
- https://bio.libretexts.org/Bookshelves/Computational_Biology/Book%3A_Computational_Biology_-_Genomes_Networks_and_Evolution_(Kellis_et_al.)/12%3A_Large_Intergenic_Non-Coding_RNAs/12.02%3A_IntroductionDNA methylation is a binary code that is effectively equivalent to turning a gene ”on” or ”off”. However, often times a gene might need to be more highly expressed as opposed to just being turned on. ...DNA methylation is a binary code that is effectively equivalent to turning a gene ”on” or ”off”. However, often times a gene might need to be more highly expressed as opposed to just being turned on. The unique combination of these two elements on a stretch of DNA can be thought of as a barcode for cell type. These histone modifications can be thought of as a type of epigenetic barcode that allows cell DNA to be scanned for types.
- https://bio.libretexts.org/Bookshelves/Computational_Biology/Book%3A_Computational_Biology_-_Genomes_Networks_and_Evolution_(Kellis_et_al.)/12%3A_Large_Intergenic_Non-Coding_RNAs/12.05%3A_Long_non-coding_RNAs_in_Epigenetic_RegulationThe skin in all parts of the body is composed of an epithelial layer and a layer of connective tissue made up of cells called fibroblasts. Research has found that the type of skin in the hands shares ...The skin in all parts of the body is composed of an epithelial layer and a layer of connective tissue made up of cells called fibroblasts. Research has found that the type of skin in the hands shares a remarkably similar epigenetic signature to the skin in the feet, which is also distally located. There exists a clear boundary between the lung cell type which is proximal to the body, and the foot cell type which is distal to the body.
- https://bio.libretexts.org/Bookshelves/Computational_Biology/Book%3A_Computational_Biology_-_Genomes_Networks_and_Evolution_(Kellis_et_al.)/10%3A_RNA_Folding/10.08%3A_Advanced_topics_Summary_and_key_points_Further_Reading_BibliographyOn the other hand some believe junk RNA might actually have an important role as signals inside the cell and all of it is actually functional, the truth probably lies somewhere in between. – Pedersen ...On the other hand some believe junk RNA might actually have an important role as signals inside the cell and all of it is actually functional, the truth probably lies somewhere in between. – Pedersen JS, Bejerano G, Siepel A, Rosenbloom K, Lindblad-Toh K, Lander ES, Kent J, Miller W, Haussler D Identication and classication of conserved RNA secondary structures in the human genome.
- https://bio.libretexts.org/Bookshelves/Computational_Biology/Book%3A_Computational_Biology_-_Genomes_Networks_and_Evolution_(Kellis_et_al.)/17%3A_Regulatory_Motifs_Gibbs_Sampling_and_EM
- https://bio.libretexts.org/Bookshelves/Computational_Biology/Book%3A_Computational_Biology_-_Genomes_Networks_and_Evolution_(Kellis_et_al.)/12%3A_Large_Intergenic_Non-Coding_RNAs/12.03%3A_Noncoding_RNAs_from_Plants_to_MammalsPlants: RNA-dependent RNA polymerase, where the polymerase takes template of RNA and make a copy of it, is available in plants but not humans, and can make small RNAs. Flies: use RNAs for an RNA switc...Plants: RNA-dependent RNA polymerase, where the polymerase takes template of RNA and make a copy of it, is available in plants but not humans, and can make small RNAs. Flies: use RNAs for an RNA switch; coordinated regulation of hox gene requires noncoding RNA. One of these is long non-coding RNAs which can be thought of as fulfilling an air traffic control function within the cell.
- https://bio.libretexts.org/Bookshelves/Computational_Biology/Book%3A_Computational_Biology_-_Genomes_Networks_and_Evolution_(Kellis_et_al.)/14%3A_MRNA_Sequencing_for_Expression_Analysis_and_Transcript_Discovery/14.01%3A_IntroductionmRNA sequencing was a daunting task, and requires approximately 40 million aligned reads in order to accurately measure mRNA transcripts.This did not become possible until 2009, when next-generation s...mRNA sequencing was a daunting task, and requires approximately 40 million aligned reads in order to accurately measure mRNA transcripts.This did not become possible until 2009, when next-generation sequencing technologies became more advanced and efficient. In this chapter, we will explore the different techniques for using mRNA sequencing data to aid in gene and transcript discovery as well as in expression analysis.
- https://bio.libretexts.org/Bookshelves/Computational_Biology/Book%3A_Computational_Biology_-_Genomes_Networks_and_Evolution_(Kellis_et_al.)/20%3A_Networks_I-_Inference_Structure_Spectral_Methods/20.07%3A_Neural_NetworksThe authors point out three diculties encountered when training models of sequence of specificities on the large volumes of sequence data produced by modern high-throughput technologies: (a) the data ...The authors point out three diculties encountered when training models of sequence of specificities on the large volumes of sequence data produced by modern high-throughput technologies: (a) the data comes in qualitatively different forms, including protein binding microarrays, RNAcompete assays, ChIP- seq and HT-SELEX, (b) the quantity of data is very large (typical experiments measure ten to a hundred thousand sequences and (c) each data acquisition technology has it’s own formats and error p…
- https://bio.libretexts.org/Bookshelves/Computational_Biology/Book%3A_Computational_Biology_-_Genomes_Networks_and_Evolution_(Kellis_et_al.)/15%3A_Gene_Regulation_I_-_Gene_Expression_Clustering
- https://bio.libretexts.org/Bookshelves/Computational_Biology/Book%3A_Computational_Biology_-_Genomes_Networks_and_Evolution_(Kellis_et_al.)/16%3A_Gene_Regulation_II_-_Classification/16.05%3A_Semi-Supervised_LearningIn some scenarios we have a data set with only a few labeled data points, a large number of unlabeled data points and inherent structure in the data. This type of scenario both clustering and classifi...In some scenarios we have a data set with only a few labeled data points, a large number of unlabeled data points and inherent structure in the data. This type of scenario both clustering and classification do not perform well and a hybrid approach is required. This semi-supervised approach could involve the clustering of data first followed by the classification of the generated clusters.
