Posts by Collection

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Portfolio item number 2

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Algebraic and Combinatorial Phylogenetics

Attended the conference and course on Semialgebraic statistics, latent tree models, and phylogenetics.

Deep Learning specialization

Took online specialization on Coursera.

ASA New Mexico Chapter Annual Meetings

Attended ASA chapter annually meetings since 2016. Gave a talk in 2018.

Evolution meetings

Gave a talk at Evolution 2019.

Joint Statistical Meetings

Presented a poster at JSM 2019.

Women in Statistics and Data Science

Attended the conference and the Introduction to Spark with R course.

New Mexico Big data and Analytics Summit

Attended the Image Analysis and Biomedical applications tracks.

Heuristics for unrooted, unranked, and ranked anomaly zones under birth-death models

In this article, we introduce several heuristic approaches to infer whether species trees are in anomaly zones when it is difficult or impossible to compute the entire distribution of gene tree topologies.

PRANC: ML species tree estimation from the ranked gene trees under coalescence

PRANC is a computational framework to work with the ranked gene trees. PRANC performs a heuristic search from the initial trees to find a ML species tree.

Probabilities of unranked and ranked anomaly zones under birth-death models

In this paper, we study how the parameters of a species tree simulated under a constant rate birth-death process can affect the probability that the species tree lies in the anomaly zone. We derive the lower bound of the probability of the species tree being in an unranked anomaly zone with n leaves for large speciation rate $\lambda$, and we show that this lower bound approaches 1 as n $\rightarrow \infty$ and $\lambda \rightarrow \infty$.

Calculating the probability of a ranked gene tree given a species tree under the multispecies coalescent model

Published: April 13, 2018

Slides

Analysis of ranked gene tree probability distributions under the coalescent process for detecting anomaly zones

Published: November 07, 2018

Poster

Heuristic approaches for ranked, unranked, and unrooted anomaly zones

Published: June 24, 2019

Slides

Using ranked gene tree distributions for detecting anomaly zone in a species tree and maximum likelihood inference

Published: July 31, 2019

Poster

Maximum Likelihood Inference of Species Trees from Ranked Gene Trees Under the Coalescent Model

Published: August 05, 2020

Topic modeling of soil microbiomes in droughted corn

Published: November 04, 2021

Intro to Statistics (Fall 2014, Spring 2015, Summer 2015, Fall 2015, Spring 2016)

Stat 145/Math 1350, UNM, Department of Mathematics and Statistics, 2016

Class Times (Spring 2016): TR 2 - 3.15
Book: The Basic Practice of Statistics (7th Edition), by Moore, Notz and Fligner
Syllabus and Schedule    

Elements of Mathematical Statistics and Probability Theory (Spring 2020)

Stat 345, UNM, Department of Mathematics and Statistics, 2020

Class Time (DSH 225): MWF 9 - 9.50 am (Zoom meeting id on learn)
Office Hours (SMLC 319): F 3.30 pm Anastasiia (Zoom id on learn)
Discussion/Tutoring (DSH 326): W 2.30 pm Hasan, F 2 pm Jared (Zoom ids on learn)
Syllabus    
Piazza link: piazza.com/unm/spring2020/stat345
Recorded Kaltura class videos, Zoom meetings ids, HWs submission : UNM Learn