Questions tagged [sequence-analysis]
Analysis of a DNA, RNA, or peptide sequence to understand its features, function, structure, or evolution.
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embeddings for representing sequences in which items also have numeric attributes/features
My data is a collection of sequences of items (or events or webpages), in which each item also has associated numeric features.
An example could be the following scenario:
An on-demand movie ...
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embedding sequences (eg. with doc2vec): do trajectories in the learned (N-dimensional embedding) vector space make any sense?
My data is a collection of temporal sequences of events (each event has a timestamp / or, alternatively, a duration).
An example could be sequences of events generated by customers interacting with ...
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Sequence analysis - adding a time vector
I'm currently attempting to define a Markov chain technique for producing high-resolution synthetic activity sequences. I'm using time-use data with a resolution of 10 minutes. According to the ...
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A method for clustering 1D signals?
I have samples from 150 different genes containing the following information:
sequence of the gene
signal strength along the length of the gene (the signal can be negative or positive).
I have ...
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Proper statistical test for NGS dataset with two samples containing a library of 12,000 sequences each sorted into 4 bins with counts in each bin
Description of the experiment:
A library containing 12,000 unique nucleotide sequences is integrated into two samples, a WT cell line and a knockout cell line. Each cell contains only one reporter ...
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In sequence analysis, my confounders should be measured at the beginning, at the end or during the length of the study time of the sequences?
I'm working on a study for analysis patterns of treatment choices via sequence analysis (discrepancy). I have sociodemographic variables (age groups, sex, etc) that I have measured from baseline but ...
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Any Model for predicting next outcome in a sequence? [closed]
I am wondering if there is any model that could recognize a pattern using only previous outcomes and their order to predict the next outcome. Here's an example of data
Game 1 - Win.
Game 2 - Win.
Game ...
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Measure prosodic similarity using deep learning
I have a dataset of 12,000 audio recordings of nonnative learners imitating the prosody of native speakers (300 samples for each native speaker utterance). All the nonnative learners' attempts were ...
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How to calculate the evaluation metrics on streaming data for online ML algorithms
I am working on a binary classification problem where I need to develop an online ML model that can work on streaming data. However, I am not sure how can I use the evaluation metrics for ...
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Predicting sequence of sets
I have dataset which contains users and their market baskets (itemsets). The goal is to predict next basket.
Can I predict next itemset in sequence of sets (itemsets) using RNN or another NN? Like ...
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Best R package for analysis of DEGs in a time-series RNA-seq?
I have been reading quite a bit in the last couple of days, but I haven't found a definitive answer.
I want to do a DE analysis of time-series RNA-seq data in R with the following restrains:
Over 6 ...
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Sequence learning from farm operations data
I need to generalize a single sequence from N sequences entailing farming tasks/operations and ultimately plotting it on Gantt chart.
There are a total let's assume N sequences = n (total fields) * t (...
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Viewing automated cost matrix for DHD in TraMineR
I'm using social sequence analysis, and comparing between different distance methods for my data. I'm wondering if there is a way to view/call the automatic substitution cost matrix that the dynamic ...
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Determining a p-value for a test statistic that depends on other test statistics
Sorry for the confusing wording of the title. If some has any better way to word it, please feel free to change it.
Background
For those unfamiliar with bioinformatics data, I have data from a ...
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What does it mean if a simple linear neural network performs better than an LSTM on sequential data?
I'm working on a genetic data project, where one data sample is represented as sequences of integers (of length 2000) and it needs to be classified into one of 4 classes, so I guess it is similar to ...
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Why shouldn't you mix variable size inputs in the same minibatch?
I am trying to build a CNN-LSTM architecure in tf.keras that classifies sequences of varying sizes. My training data is highly variable and I would have to crop/pad sequences in order to create ...
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Order of convergence of a product of two convergent sequences
Let $a_n$ be a sequence that converges to $A$ with order of $n^\alpha$, that is $a_n = A + \mathcal{O}(n^\alpha)$ and $b_n$ is another sequence that converges to B with order of $n^\beta$; i.e. $b_n = ...
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Choosing a model for input: categorised, weighted sequence, output: binary variable
What would be an appropriate model for predicting a binary target variable, given a weighted sequence?
Sequences will be reasonably short, typically between ~ 1 and 5 elements. I have in the order of ...
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Neural network to generate barcodes
I am working on a problem regarding barcodes. This is my first time using sequence models practically. Summarizing it:
I have 681 32 character, case-insensitive, alphanumeric strings that are ...
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Self Attention for Variable Length Sequence Classification
I have a problem that is not particularly unique, but I'm still having trouble to figure out exactly how it's usually done.
My training set is of the form $\mathcal{T}=\{(t_i\in \mathbb{R}^{[n,m]\...
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What are the classifiers that can be used for sequence data?
I've been going through the classifiers like Naive Bayes, Decision Tree etc. I've a sequence data like so
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Training and testing transformer model from scratch
As you know, transformers are one of the strongest model in the field of NLP and machine translation.
I know there are many resources, but I still could not find a good tutorial teaching how to use ...
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Training two Hidden markov models vs two state Hidden Markov models
I have a scenario where I have log of events followed by some kind of special event (e.g Failure etc). I have two kind of sequences (events, that are observations, can be common in both sequence), ...
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Is LSTM (Long Short-Term Memory) dead?
From my own experience, LSTM has a long training time, and does not improve performance significantly in many real world tasks.
To make the question more specific, I want to ask when LSTM will work ...
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Sequences comparison metrics
I know about Edit distance, Longest Common Subsequence and their normalized versions to measure the similarity between sequences But do we have any similarity measures other than the above ones?
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How To Solve A Sequence Question [closed]
I'm taking a course on R on edx, but I have been stocked here for days. Please
Which integer values are between the maximum and minimum heights? For example, if the minimum height is 10.2 and the ...
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How is conditioning on a variable different than specifying nested random effects
How is conditioning on a variable similar to or different from using a mixed effect model?
I am a biologist. I'm analyzing my data. I have body sites nested within individuals. We're interested in ...
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Predicting the Winner of a sequence of numbers
I have various series of numbers of different lengths (ranging from 4 to 10) such as the example below:
[1.5, 5.0, 6.0, 6.0, 8.0]
[1.4, 6.0, 7.5, 9.0, 50.0, 100.0, 200.0]
For each one of them I ...
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On the convergence of infinite sum of a hypergeometric function resulted from a nested sum
I am interested in finding the CDF of the sum $U=\sum_{i=0}^N U_i$ where:
$$F_{U_i}(x)=\sum_{n=0}^\infty \frac {2(-1)^nR^{k\alpha+n\alpha}x^{k+n}}{\Gamma(k)n!\theta^{k+n}(k+n)(k\alpha+n\alpha+2)}$$
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Can LSTMs classify multivariate time sequences?
I've been learning about LSTMs and I commonly see them applied to the same type of task. For example, given a 1D list of values, predict which class they belong to. Or, given 8 values from 8 sensors, ...
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Analyse set of Sequences of varying length with PCA?
Task description
I have a dataset with strings indicating the sequence of the screens a user visit when making a purchase on an app.
A string could be: "1,2,1,2,3,3,4,5,6,7,3,2,5,6". Another string ...
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Binary Sequence Prediction Model with Time dependant features
I got a very long sequence of binary items (0 or 1). Each item is associated to a timestamp. For example :
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Likelihood Matrix from a Random Forest?
I'm going through the supporting material of a paper (https://science.sciencemag.org/content/360/6384/81) , trying to reproduce their results (see below, note that HVG=highly variable gene). The data ...
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Ideas for determining the optimal sequence of calls and emails to maximize the probability of a sales lead converting to a sale?
I have a large data set of sales leads that are in the form of a lead_id, a sequence of binary integers that denote the order of emails and phone calls made to a sales lead, and the binary outcome of ...
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have many error likelihoods, how to combine to get a confidence or p value?
I'm working in bioinformatics and its been a long time since I dusted on my statistics. Basically I'm working on variant calling which amounts to sequencing a large number of sequence reads and ...
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Which distance metric to use to cluster categorical sequences (clickstreams or clickpaths)?
For my research, I want to cluster website visitors based on their clickstreams to understand different information behavior patterns (i.e., customer/visitor journeys). The data can be characterized ...
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ATGC sequence of gene expression data [closed]
I am not a pro in genetics so please excuse my non-technical language.
I need dataset which contains the gene expression as well as the associated ATGC sequence with each gene expression value. For ...
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Handling missing data in Sequence Analysis (TraMineR) within the observation window
I´m using sequence analysis. I have a question about how to deal with missing data within the observation window. The starting point of the analysis is when respondents leave secondary school (t0). I ...
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Unsupervised clustering of sequence of events to subsequences
I have a big dataset of M sequences of [1 - N] events, where each event has multiple properties (start date, end date, location, ...
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Combining probabilities to find most probable window
I have a series of observations, with an associated probability that an event is occuring at timestep t, something like:
[0.8, 0.8, 0.3, 0.9, 0.2]
Events can ...
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How to understand "multimodal" RNNs for image captioning?
This paper Deep Visual-Semantic Alignments for Generating Image Descriptions on image captioning proposed a Multimodal Recurrent Neural Network architecture.
From my understanding, the multimodal RNN ...
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Localized distance function on sequential binary data
I am trying to find a good distance function for sequential data that is all binary. For now, I am using Edit distance however I have some more domain-specific knowledge that I would like to ...
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Sequence prediction based on non-sequential inputs
I have a dataset with timestamps and event values (true or false -- these are based on sensor data which detect room occupancy). I'd like to build a model that would take a timestamp as an input and ...
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What are the algorithms for fusing time series together [closed]
Assume I have multiple time series with the same length and the same range. What are the different algorithm used to fuse the time series together? what techniques would the best to combine them to ...
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Probability of Finding Two Matching Subsequences in a Sequence
I'm currently studying DNA sequencing and am trying to find a formula which gives the probability that a subsequence of length $k$ appears twice in a sequence of $L$ bases (characters); this is pretty ...
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Estimation of partitioning error in next-generation sequencing experiments
[Edited: explanation of the partitioning error]
I would like to estimate how the initial number of molecules (or the level of gene expression) affects reproducibility between technical replicates of ...
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Is there a canonical probability distribution on an ordering/permutation
What is a good way of defining a non-uniform probability distribution on a permutation of k objects?
For example, suppose the parameter was an ideal ordering, and the probability of an ordering was ...
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Using deep learning to measure the similarity between two variable length voice sequences
Usually we use DTW (Dynamic Time warpping) to measure the similarity between two variable voice sequences. However DTW is time-consuming and not easy to run in the GPU since too much control in it. I ...
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Is Length Normalization used in each step of Beam Search?
In Andrew Ng's lesson on refining Beam Search, it seems that Length Normalization is used ONLY AFTER LAST STEP of Beam Search, that is, when the B most probable sequences have been generated. My ...
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How to stretch a time series to any length, n, without padding? [duplicate]
What algorithms are most suitable if I want to strect a time series to a certain length, n. I dont want to just pad the time series with values at the beginning or end, I want the pattern of the data ...
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