Francisco Requena
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API (1)
R (8)
animation (4)
bayesian (1)
bias (1)
drug-discovery (1)
genetics (1)
human-genetics (1)
machine-learning (2)
networks (1)
statistics (2)
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Human genetics as a tool for drug discovery

drug-discovery
human-genetics
For children with a rare disease, an accurate diagnosis is crucial to provide advice, possible therapies and assess the potential risk for family members in future generations. Public initiatives such as the International Rare Diseases Research Consortium (IRDiRC) set the goal for 2017-2027 to “enable all people living with a rare disease to receive an accurate diagnosis, care, and available therapy soon after seeking medical care” (1).
Jul 11, 2022
Francisco Requena

How many genes have been associated with cancer in PubMed?

API
R
bias
In the biomedical literature, it is common to find sentences like:
Mar 20, 2021
Francisco Requena

Extracting gene panels from the Genomics England Panelapp

web-scrapping
R
genetics
The Genomics England PanelApp provides panels of genes related to human disorders manually curated by healthcare experts. From a clinical and research perspective, this is a remarkable resource. At the time of writing this post, over 320 panels have been published.
Mar 20, 2021
Francisco Requena

An introduction to ROC curves with animated examples

animation
R
machine-learning
Receiver operating characteristic (ROC) curves is one of the concepts I have struggled most. As a personal view, I do not find it intuitive or clear at first glance. Possibly, because we are used to interpreting information as single values, such as mean, median, accuracy…ROC curves are different because it represents a group of values conforming a curve. Besides, it is the most popular way to represent a model performance for a particular dataset where the task is a binary classification.
Jun 12, 2020
Francisco Requena

An introduction to uncertainty with Bayesian models

animation
R
statistics
bayesian
In this post, we will get a first approximation to the “uncertainty” concept. First, we will train two models: logistic regression and its “Bayesian version” and compare their performance. Furthermore, we will explore the advantage of using a Bayesian model when we want to estimate how likely is our prediction. Finally, we will briefly discuss why there are some predicted values more probable than others.
May 29, 2020
Francisco Requena

Poisson distribution in genomics

animation
R
statistics
In this post, I will discuss briefly what is the Poisson distribution and describe two examples extracted from research articles in the genomics field. One of them based on the distribution of structural variants across the genome and other about de novo variants in a patient cohort.
May 14, 2020
Francisco Requena

Estimating pi value with Monte Carlo simulation

animation
R
Mar 5, 2020
Francisco Requena

Exploring world flights with networks

networks
R
Recently, I started to read this free accessible book written by Albert-László Barabási. In the Chapter 4 of his book, it depicts the USA airport networks to represent scale-free networks. I was wondering if we can get a world picture, creating the same network but including the global routes using open data from internet.
May 1, 2019
Francisco Requena

Prediction of dengue cases through climate variables

machine-learning
R
Recently, I discovered a new website about competitions that it is not called Kaggle! Its name is Drivendata.
Dec 9, 2017
Francisco Requena
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