Lecture 6a: Introduction to Hidden Markov Models

• Select a basic method to model a sequence family – what are the states, what are the emitted symbols. • Using a training set – a set of known sequences in the family – estimate the parameters of the model: emission and transition probabilities.

  Introduction, Methods

Hamilton Depression Rating Scale (HDRS)

Hamilton Depression Rating Scale (HDRS) Hamilton Depression Rating Scale (HDRS) Study Identification tool Comparator/ caseness Population Results Community Stukenberg et al., 1990 Quality assessed: + HDRS DSM-III-R (SCID) N=177 community dwelling adults over 55 years, age

  Scale, Ratings, Hamilton, Depression, Hamilton depression rating scale, Hdrs

Lecture 8:Motifs and Motifs finding

Motifs • Motif is a region (a subsequence) of protein or DNA sequence that has a specific structure • Motifs are candidates for functionally

  Lecture, Findings, Lecture 8, Motifs, Motifs and motifs finding

Lecture 7 Protein-Protein Interaction

the DNA-binding domain (DB: blue circle) and one that contains an activation domain (AD: half blue circle), are co-transfected into an appropriate host strain. (C) If the fusion partners (yellow and red) interact, the DB and AD are brought into proximity and can activate transcription of reporter genes (here LacZ).

  Binding

Lecture 10 : Whole genome sequencing and analysis

Polymorphism (SNP): a variation is a single nucleotide in a genome • Typically we have two say alleles (here C and T) minor (less common) and major. • minor allele frequency - the ratio of chromosomes in the population carrying the less common variant to those with the more common variant • A second generation human

  Polymorphisms

CareStart COVID-19 Antigen test - Fact Sheet for Patients

test. This Fact Sheet contains information to help you understand the risks and benefits of using this test for the diagnosis of COVID-19. After reading this Fact Sheet, if you have questions or would like to discussthe information provided, please talk to your healthcare . provider. For the most up to date information on COVID-

  Tests, Sheet

Lecture 2 Pairwise sequence alignment.

Discovering sequence similarity by dot plots Given are two sequence lengths n and m respectively. Do they share a similarity and if so in which region? Dot-plot method: make n x m matrix with D and set D(i,j) = 1 if amino-acid (or nucleotide) position i in first sequence is the same (or similar as described later) as the amino-acid

Lecture 11 Phylogenetic trees

Version parsimony models: • Character states – Binary: states are 0 and 1 usually interpreted as presence or absence of an attribute (eg. character is a gene and can be

Annex 1. Example of the semi‐structured interview guide

Annex 1. Example of the semi-­‐structured interview guide V. iral Hepatitis: Semi-structured interview M / F. Provider / community member / both. Age. Region. 1. …

  Annex, Annex 1

Lecture 5: Multiple sequence alignment

Multiple alignment as generalization of pairwise alignment S1,S2,…,Sk a set of sequences over the same alphabet As for the pair-wise alignment, the goal is to find alignment that maximizes some scoring function:

  Multiple

Forecasting the Supply of Human Resources - Jiwaji University

A transition matrix, or Markov matrix, can be used to model the internal flow of human resources. These matrices simply show as probabilities the average rate of historical movement from one job to another. To determine the probabilities of job incumbents remaining in their jobs for the forecasting period. Example -

  Transition, Matrices, Probabilities

Lecture 2: Markov Decision Processes - David Silver

State Transition Matrix For a Markov state s and successor state s0, the state transition probability is de ned by P ss0= P S t+1 = s 0jS t = s State transition matrix Pde nes transition probabilities from all states s to all successor states s0, to P = from 2 6 4 P 11::: P 1n... P n1::: P nn 3 7 5 where each row of the matrix sums to 1.

  Transition, Probabilities, Transition probabilities

Monte Carlo Methods and Importance Sampling

This can be computed exactly by multiplying transition probability matrices together, or by employing the Baum (1972) algorithm (which you will learn about later), but it can also be approximated by Monte Carlo. It is simple to simulate genetic drift in a Wright-Fisher population; thus we can easily simulate values for X tgiven X 0 = x 0. Then ...

  Transition, Importance, Sampling, Matrices, Importance sampling

Elements of Dirac Notation - College of Saint Benedict and ...

state in some transition or event. The bra represents the final state or the language in which you wish to express the content of the ket . For example, is the probability amplitude that a particle inx =Ψ.25 state Q will be found at position x = .25. In conventional notation we write this as Q (x=.25), the value of the function Q at x = .25 ...

  Transition, Notation, Carid, Dirac notation