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
Elementary methods provide more replicable results in microbial differential abundance analysis
Pelto
J,
Auranen
K,
Kujala
J &
Lahti
L.
arXiv
2024
10.48550/arXiv.2404.02691
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URL
FdeSolver: A Julia Package for Solving Fractional Differential Equations
Khalighi
M,
Benedetti
G &
Lahti
L.
arXiv arXiv,
2022
Preprint
10.48550/ARXIV.2212.12550
|
URL
Impacts of maternal microbiota and microbial metabolites on fetal intestine, brain and placenta
Husso
A,
Pessa-Morikawa
T,
Koistinen
V,
Karkkainen
O,
Lahti
L,
Iivanainen
A,
Hanhineva
K &
Niku
M.
bioRxiv Cold Spring Harbor Laboratory,
2022
10.1101/2022.07.01.498433
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URL
The gut microbiome is a significant risk factor for future chronic lung disease
Liu
Y,
Teo
S,
Meric
G,
Tang
H,
Zhu
Q,
Sanders
J,
Vazquez-Baeza
Y,
Verspoor
K,
Vartiainen
V,
Jousilahti
P,
Lahti
L,
Niiranen
T,
Havulinna
A,
Knight
R,
Salomaa
V &
Inouye
M.
2022
Preprint
URL