Our research focuses on computational analysis of
complex natural and social systems. There is a great demand for
targeted computational techniques to extract information and insights
from rich data collections based on clever combinations of human and
machine intelligence. We blend elements from fields such as machine
learning/AI, probabilistic programming, statistical ecology, and data
science, and drive open developer communities that help to translate
latest theoretical advances into accessible methods to inform
modeling, experimentation, and decision-making. For a full list of publications check this page.
Preprints
Learning and teaching biological data science in the bioconductor community
Drnevich
J,
Tan
F,
Almeida-Silva
F,
Castelo
R,
Culhane
A,
Davis
S,
Doyle
M,
Holmes
S,
Lahti
L,
Mahmoud
A,
Nishida
K,
Ramos
M,
Rue-Albrecht
K,
Shih
D,
Gatto
L &
Soneson
C.
arXiv
2024
10.48550/arXiv.2410.01351
Biochemical analyses can complement sequencing-based ARG load monitoring: A case study in indian hospital sewage networks
Bhanushali
S,
Parnanen
K,
Mongad
D,
Dhotre
D &
Lahti
L.
medRxiv
2024
10.1101/2024.05.31.24308262