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Succinct Data Structure
Succinct Data Structure

... Davoodi et al. showed how to support select-inorder for binary tree We simply plug our compression into this framework Need to support two additional operations: is_chain_prefix/suffix Decompress fingerprints, use lookup tables: tree + inorder position ...
Conservation genetics of the endangered grassland earless dragon
Conservation genetics of the endangered grassland earless dragon

... et al. 1994). Following elimination of alignment gaps, aligned sequences then were translated into amino acid sequences using the vertebrate mitochondrial genetic code. This was done to determine if these data were truly mitochondrial in origin. No premature stop codons were observed therefore we co ...
Diapositiva 1
Diapositiva 1

Essential Knowledge 1.B.1
Essential Knowledge 1.B.1

cluster analysis I
cluster analysis I

... 1. EM algorithm to maximize the mixture likelihood. 2. Model selection: Bayesian Information Criterion (BIC) for determining k and the complexity of the covariance matrix. ...
1 Time-Integrators
1 Time-Integrators

Motifs and motif prediction methods I - BIDD
Motifs and motif prediction methods I - BIDD

... A possible HMM for the sequence “ACCY” which is represented as a sequence of probabilities. The probability of ACCY is shown as a highlighted path through the model. P that an amino acid occurs in a particular state ...
Evaluation of the phylogenetic position of the planctomycete
Evaluation of the phylogenetic position of the planctomycete

124370-hw2-1-
124370-hw2-1-

biopatt - Carnegie Mellon School of Computer Science
biopatt - Carnegie Mellon School of Computer Science

G070840-00 - DCC
G070840-00 - DCC

Example - Ukrainian Risk Laboratory
Example - Ukrainian Risk Laboratory

... Real time GPU accelerated Monte Carlo method. (about 1 second for billions of trajectories) And at last User friendly interface turns RMS 0.2 in a very efficient and nice system  ...
Enhanced Bug Detection by Data Mining Techniques
Enhanced Bug Detection by Data Mining Techniques

... V. Neelima, Annapurna. N, V. Alekhya, Dr. B. M. Vidyavathi “Bug Detection through Text Data Mining”, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 3, Issue 5, May2013.radio centric overlay-underlay waveform,” in Proc. 3rd Anuja Priyama*, Abhijeeta, R ...
Phylogenetic Relationship Among Some Species of Bruchinae
Phylogenetic Relationship Among Some Species of Bruchinae

... developmental stages co-exist. In this study 12SrRNA and 16SrRNA gene fragments were used to analyze the phylogeneytic relationship of two of these species i.e. Callosobruchus analis and Callosobruchus maculatus with the other Bruchid species found worldwide. The sequences showed an A+T bias of >70% ...
Comparative Methods for the Analysis of Gene
Comparative Methods for the Analysis of Gene

... 1998). To facilitate comparison among different gene families, we used the same model for all analyses, even though it may not be best fit for every gene family analysis. Because we had no information on outgroups for the gene families in question, we used midpoint rooting. Another possible approach ...
Lecture 19 (Mar. 24)
Lecture 19 (Mar. 24)

... known or not easily measured. a. Generalized Monte Carlo algorithm: 1. Generate a random number 2. “Guess” within some constraints or boundary on the problem i.e. mapping f(x) to coordinate space (Figure 1). 3. Cost function: “Is the point inside the relevant coordinate space?” 4. If yes, store valu ...
No Slide Title
No Slide Title

Sequence editing and analysis PDF
Sequence editing and analysis PDF

... read and CO1F is the forward read (usually 5’ – 3’) of the coxI gene region. We can ignore the next two pieces of information (032_A16) – they are for the sequencing laboratory -- and .ab1 indicates it comes from the automated ABI sequencer. 2. Highlight both sequences (click and hold the shift key, ...
1 The Likelihood Principle
1 The Likelihood Principle

this PDF file
this PDF file

... of these parameters should be guided by the data analyst, and performance of the system may vary based on different parameter values. However, the above chosen parameter values seemed to work reasonably well for our experimental setup and a slight variation from the above specified values did not se ...
scores
scores

Clustering / Scaling
Clustering / Scaling

... • K-means is much faster than hierarchical – Does not compute the distances between all pairs ...
a note on robust estimation in logistic regression model - DML-PL
a note on robust estimation in logistic regression model - DML-PL

... other estimation methods. The ’cubif’ procedure showed similar results. Also changes in sample size from 100 to 500 did not essentially changed the situation. We can see that as the contamination values increase, the standard robust methods start to work better. However, they seem to achieve the eff ...
1 Gene trees and species trees The lines of organismal descent that
1 Gene trees and species trees The lines of organismal descent that

... very distant past. This principle can be taken a step further: all the homologous nucleotides in the current generation will ultimately coalesce to a single ancestral lineage. As a general rule, the smaller the population, the more quickly coalescence occurs. Thus in a small population lineage, you ...
PANTHER version 11: expanded annotation data from Gene
PANTHER version 11: expanded annotation data from Gene

< 1 ... 20 21 22 23 24 25 26 27 28 ... 60 >

Computational phylogenetics

Computational phylogenetics is the application of computational algorithms, methods, and programs to phylogenetic analyses. The goal is to assemble a phylogenetic tree representing a hypothesis about the evolutionary ancestry of a set of genes, species, or other taxa. For example, these techniques have been used to explore the family tree of hominid species and the relationships between specific genes shared by many types of organisms. Traditional phylogenetics relies on morphological data obtained by measuring and quantifying the phenotypic properties of representative organisms, while the more recent field of molecular phylogenetics uses nucleotide sequences encoding genes or amino acid sequences encoding proteins as the basis for classification. Many forms of molecular phylogenetics are closely related to and make extensive use of sequence alignment in constructing and refining phylogenetic trees, which are used to classify the evolutionary relationships between homologous genes represented in the genomes of divergent species. The phylogenetic trees constructed by computational methods are unlikely to perfectly reproduce the evolutionary tree that represents the historical relationships between the species being analyzed. The historical species tree may also differ from the historical tree of an individual homologous gene shared by those species.Producing a phylogenetic tree requires a measure of homology among the characteristics shared by the taxa being compared. In morphological studies, this requires explicit decisions about which physical characteristics to measure and how to use them to encode distinct states corresponding to the input taxa. In molecular studies, a primary problem is in producing a multiple sequence alignment (MSA) between the genes or amino acid sequences of interest. Progressive sequence alignment methods produce a phylogenetic tree by necessity because they incorporate new sequences into the calculated alignment in order of genetic distance.
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