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.
Microbiome data science: selected examples
Taxonomic signatures of cause-specific mortality risk in human gut microbiome
Salosensaari*
A,
Laitinen*
V,
Havulinna
A,
Meric
G,
Cheng
S,
Perola
M,
Valsta
L,
Alfthan
G,
Inouye
M,
Watrous
J,
Long
T,
Salido
R,
Sanders
K,
Brennan
C,
Humphrey
G,
Sanders
J,
Jain
M,
Jousilahti
P,
Salomaa
V,
Knight
R,
Lahti*
L &
Niiranen*
T.
Nature Communications 12,
2021
10.1038/s41467-021-22962-y
Statistical and machine learning techniques in human microbiome studies: Contemporary challenges and solutions
Moreno-Indias
I,
Lahti
L,
Nedyalkova
M,
Elbere
I,
Roshchupkin
G,
Adilovic
M,
Aydemir
O,
Bakir-Gungor
B,
Pau
E,
D’Elia
D,
Desai
M,
Falquet
L,
Gundogdu
A,
Hron
K,
Klammsteiner
T,
Lopes
M,
Zambrano
L,
Marques
C,
Mason
M,
May
P,
Pašić
L,
Pio
G,
Pongor
S,
Promponas
V,
Przymus
P,
Sáez-Rodríguez
J,
Sampri
A,
Shigdel
R,
Stres
B,
Suharoschi
R,
Truu
J,
Truică
C,
Vilne
B,
Vlachakis
D,
Yılmaz
E,
Zeller
G,
Zomer
A,
Gómez-Cabrero
D &
Claesson
M.
Frontiers in Microbiology 12,
2021
10.3389/fmicb.2021.635781
Microbiome data science in the SummarizedExperiment universe
Lahti
L,
Ernst
F,
Shetty
S &
others.
F1000Research 10(748),
2021
(slides); version 1; not peer reviewed
10.7490/f1000research.1118712.1
Modeling spatial patterns in host-associated microbial communities
Ruuskanen
M,
Sommeria-Klein
G,
Havulinna
A,
Niiranen
T &
Lahti
L.
Environmental Microbiology 23(5),
2021
10.1111/1462-2920.15462
Microbial communities as dynamical systems
Gonze
D,
Coyte
K,
Lahti
L &
Faust
K.
Current Opinion in Microbiology 44,
2018
10.1016/j.mib.2018.07.004
|
PDF
Multi-stability and the origin of microbial community types
Gonze
D,
Lahti
L,
Raes
J &
Faust
K.
ISME Journal 11,
2017
10.1038/ismej.2017.60
|
PDF
Signatures of ecological processes in microbial community time series
Faust
K,
Bauchinger
F,
Laroche
B,
Buyl
S,
Lahti
L,
Washburne
A,
Gonze
D &
Widder
S.
Microbiome 6(120),
2018
10.1186/s40168-018-0496-2
|
PDF
Linking statistical and ecological theory: Hubbell’s unified neutral theory of biodiversity as a hierarchical dirichlet process
Harris
K,
Parsons
T,
Ijaz
U,
Lahti
L,
Holmes
I &
Quince
C.
Proceedings of the IEEE 105(3),
2017
10.1109/JPROC.2015.2428213
|
PDF
More microbiome data science and life science applications
Examining the healthy human microbiome concept
Joos
R,
Boucher
K,
Lavelle
A,
Arumugam
M,
Blaser
M,
Claesson
M,
Clarke
G,
Cotter
P,
Sordi
L,
Dominguez-Bello
M,
Dutilh
B,
Ehrlich
S,
Ghosh
T,
Hill
C,
Junot
C,
Lahti
L,
Lawley
T,
Licht
T,
Maguin
E,
Makhalanyane
T,
Marchesi
J,
Matthijnssens
J,
Raes
J,
Ravel
J,
Salonen
A,
Scanlan
P,
Shkoporov
A,
Stanton
C,
Thiele
I,
Tolstoy
I,
Walter
J,
Yang
B,
Yutin
N,
Zhernakova
A,
Zwart
H,
,
Doré
J &
Ross
R.
Nature Reviews Microbiology
2024
10.1038/s41579-024-01107-0
Regular exercise training induces more changes on intestinal glucose uptake from blood and microbiota composition in leaner compared to heavier individuals in monozygotic twins discordant for BMI
Lietzén
M,
Guzzardi
M,
Ojala
R,
Hentilä
J,
Heiskanen
M,
Honkala
S,
Lautamäki
R,
Löyttyniemi
E,
Kirjavainen
A,
Rajander
J,
Malm
T,
Lahti
L,
Rinne
J,
Pietiläinen
K,
Iozzo
P &
Hannukainen
J.
Nutrients 16,
2024
10.3390/nu16203554
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
Effects of obesity and exercise on hepatic and pancreatic lipid content and glucose metabolism: PET-studies in twins discordant for BMI
Lietzén
M,
Mari
A,
Ojala
R,
Hentilä
J,
Koskensalo
K,
Lautamäki
R,
Löyttyniemi
E,
Parkkola
R,
Saunavaara
V,
Kirjavainen
A,
Rajander
J,
Malm
T,
Lahti
L,
Rinne
J,
Pietiläinen
K,
Iozzo
P &
Hannukainen
J.
Biomolecules 14(9),
2024
10.3390/biom14091070
A cohort study in family triads: Impact of gut microbiota composition and early life exposures on intestinal resistome during the first two years of life
Jokela
R,
Pärnänen
K,
Ponsero
A,
Lahti
L,
Kolho
K,
Vos
W &
Salonen
A.
Gut Microbes 16(1),
2024
10.1080/19490976.2024.2383746
Associations between gut microbiota and incident fractures in the FINRISK cohort
Grahnemo
L,
Kambur
O,
Lahti
L,
Jousilahti
P,
Niiranen
T,
Knight
R,
Salomaa
V,
Havulinna
A &
Ohlsson
C.
npj Biofilms and Microbiomes 10(69),
2024
10.1038/s41522-024-00530-8
Multikingdom oral microbiome interactions in early-onset cryptogenic ischemic stroke
Manzoor
M,
Leskelä
J,
Pietiäinen
M,
Martinez-Majander
N,
Ylikotila
P,
Könönen
E,
Niiranen
T,
Lahti
L,
Sinisalo
J,
Putaala
J,
Pussinen
P &
Paju
S.
ISME Communications 4(1),
2024
10.1093/ismeco/ycae088
Association between butyrate-producing gut bacteria and the risk of infectious disease hospitalisation: Results from two observational, population-based microbiome studies
Kullberg
R,
Wikki
I,
Haak
B,
Kauko
A,
Galenkamp
H,
Peters-Sengers
H,
Butler
J,
Havulinna
A,
Palmu
J,
McDonald
D,
Benchraka
C,
Abdel-Aziz
M,
Prins
M,
Maitland van der Zee
A,
Born
B,
Jousilahti
P,
Vos
W,
Salomaa
V,
Knight
R,
Lahti
L,
Nieuwdorp
M,
Niiranen
T &
Wiersinga
W.
The Lancet Microbe
2024
https://doi.org/10.1016/S2666-5247(24)00079-X
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
A concept for international societally relevant microbiology education and microbiology knowledge promulgation in society
Timmis
K,
Hallsworth
J,
McGenity
T,
Armstrong
R,
Colom
M,
Karahan
Z,
Chavarría
M,
Bernal
P,
Boyd
E,
Ramos
J,
Kaltenpoth
M,
Pruzzo
C,
Clarke
G,
López-Garcia
P,
Yakimov
M,
Perlmutter
J,
Greening
C,
Eloe-Fadrosh
E,
Verstraete
W,
Nunes
O,
Kotsyurbenko
O,
Nikel
P,
Scavone
P,
Lavigne
M,
Roux
F,
Timmis
J,
Parro
V,
Michán
C,
García
J,
Casadevall
A,
Payne
S,
Frey
J,
Koren
O,
Prosser
J,
Lahti
L,
Lal
R,
Anand
S,
Sood
U,
Offre
P,
Bryce
C,
Mswaka
A,
Jores
J,
Kaçar
B,
Blank
L,
Maaßen
N,
Pope
P,
Banciu
H,
Armitage
J,
Lee
S,
Wang
F,
Makhalanyane
T,
Gilbert
J,
Wood
T,
Vasiljevic
B,
Soberón
M,
Udaondo
Z,
Rojo
F,
Tamang
J,
Giraud
T,
Ropars
J,
Ezeji
T,
Müller
V,
Danbara
H,
Averhoff
B,
Sessitsch
A,
Partida-Martínez
L,
Huang
W,
Molin
S,
Junier
P,
Amils
R,
Wu
X,
Ron
E,
Erten
H,
Martinis
E,
Rapoport
A,
Öpik
M,
Pokatong
W,
Stairs
C,
Amoozegar
M &
Serna
J.
Microbial Biotechnology 17(5),
2024
10.1111/1751-7915.14456
Microbiome confounders and quantitative profiling challenge predicted microbial targets in colorectal cancer development
Tito
R,
Verbandt
S,
Vazquez
M,
Lahti
L,
Verspecht
C,
Lloréns-Rico
V,
Vieira-Silva
S,
Arts
J,
Falony
G,
Dekker
E,
Reumers
J,
Tejpar
S &
Raes
J.
Nature Medicine
2024
10.1038/s41591-024-02963-2
Fecal microbiota profiles of growing pigs and their relation to growth performance
König
E,
Beasley
S,
Heponiemi
P,
Kivinen
S,
Räkköläinen
J,
Salminen
S,
Collado
M,
Borman
T,
Lahti
L,
Piirainen
V,
Valros
A &
Heinonen
M.
PLoS One 19,
2024
10.1371/journal.pone.0302724
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
|
URL
Shotgun metagenomic analysis of the oral microbiome in gingivitis: A nested case-control study
Manzoora
M,
Leskelä
J,
Pietiäinen
M,
Martinez-Majander
N,
Könönen
E,
Niiranen
T,
Lahti
L,
Sinisalo
J,
Putaala
J,
Pussinen
P &
Paju
S.
Journal of Oral Microbiology (ZJOM) 16,
2024
10.1080/20002297.2024.2330867
Integration of polygenic and gut metagenomic risk prediction for common diseases
Liu
Y,
Ritchie
S,
Teo
S,
Ruuskanen
M,
Kambur
O,
Zhu
Q,
Sanders
J,
Vázquez-Baeza
Y,
Verspoor
K,
Jousilahti
P,
Lahti
L,
Niiranen
T,
Salomaa
V,
Havulinna
A,
Knight
R,
Méric
G &
Inouye
M.
Nature Aging
2024
10.1038/s43587-024-00590-7
Gut microbiome-derived bacterial extracellular vesicles in patients with solid tumours
Mishra
S,
Tejesvi
M,
Hekkala
J,
Turunen
J,
Kandikanti
N,
Kaisanlahti
A,
Suokas
M,
Leppä
S,
Vihinen
P,
Kuitunen
H,
Sunela
K,
Koivunen
J,
Jukkola
A,
Kalashnikov
I,
Auvinen
P,
Kääriäinen
O,
Medina
T,
Medina
O,
Saarnio
J,
Meriläinen
S,
Rautio
T,
Aro
R,
Häivälä
R,
Suojanen
J,
Laine
M,
Erawijattari
P,
Lahti
L,
Karihtala
P,
Ruuska
T &
Reunanen
J.
Journal of Advanced Research
2024
Available online 7 March 2024
10.1016/j.jare.2024.03.003
Association of long-term habitual dietary fiber intake since infancy with gut microbiota composition in young adulthood
Heiskanen
M,
Aatsinki
A,
Hakonen
P,
Kartiosuo
N,
Munukka
E,
Lahti
L,
Keskitalo
A,
Huovinen
P,
Niinikoski
H,
Viikari
J,
Rönnemaa
T,
Lagström
H,
Jula
A,
Raitakari
O,
Rovio
S &
Pahkala
K.
The Journal of Nutrition 154,
2024
Available online 12 January 2024
10.1016/j.tjnut.2024.01.008
Bone marrow metabolism is affected by body weight and response to exercise training varies according to anatomical location
Ojala
R,
Hentilä
J,
Lietzén
M,
Arponen
M,
Heiskanen
M,
Honkala
S,
Virtanen
H,
Koskensalo
K,
Lautamäki
R,
Löyttyniemi
E,
Parkkola
R,
Heinonen
O,
Malm
T,
Lahti
L,
Rinne
J,
Eskola
O,
Rajander
J,
Pietiläinen
K,
Kaprio
J,
Ivaska
K &
Hannukainen
J.
Diabetes, Obesity and Metabolism 16,
2024
First published 11 October 2023
10.1111/dom.15311
Daily skin-to-skin contact alters microbiota development in healthy full-term infants
Eckermann
H,
Meijer
J,
Cooijmans
K,
Lahti
L &
Weerth
C.
Gut Microbes 16(2295403, 1),
2024
10.1080/19490976.2023.2295403
Fewer culturable Lactobacillaceae species identified in faecal samples of pigs performing manipulative behaviour
König
E,
Heponiemi
P,
Kivinen
S,
Räkköläinen
J,
Beasley
S,
Borman
T,
Collado
M,
Hukkinen
V,
Junnila
J,
Lahti
L,
Norring
M,
Piirainen
V,
Salminen
S,
Heinonen
M &
Valros
A.
Scientific Reports 14(132),
2024
10.1038/s41598-023-50791-0
Infant gut microbiota and negative and fear reactivity
Huovinen
V,
Aatsinki
A,
Kataja
E,
Munukka
E,
Keskitalo
A,
Lamichhane
S,
Raunioniemi
P,
Bridgett
D,
Lahti
L,
O’Mahony
S,
Dickens
A,
Korja
R,
Karlsson
H,
Nolvi
S &
Karlsson
L.
Development and Psychopathology
2023
10.1017/S0954579423001396
A toolbox of machine learning software to support microbiome analysis
Marcos-Zambrano
L,
López-Molina
V,
Bakir-Gungor
B,
Frohme
M,
Karaduzovic-Hadziabdic
K,
Klammsteiner
T,
Ibrahimi
E,
Lahti
L,
Loncar-Turukalo
T,
Dhamo
X,
Simeon
A,
Nechyporenko
A,
Pio
G,
Przymus
P,
Sampri
A,
Trajkovik
V,
Lacruz-Pleguezuelos
B,
Aasmets
O,
Araujo
R,
Anagnostopoulos
I,
Aydemir
Ö,
Berland
M,
Calle
M,
Ceci
M,
Duman
H,
Gündoğdu
A,
Havulinna
A,
Bra
K,
Kalluci
E,
Karav
S,
Lode
D,
Lopes
M,
May
P,
Nap
B,
Nedyalkova
M,
Paciência
I,
Pasic
L,
Pujolassos
M,
Shigdel
R,
Susín
A,
Thiele
I,
Truică
C,
Wilmes
P,
Yilmaz
E,
Yousef
M,
Claesson
M,
Truu
J &
Santa Pau
E.
Frontiers in Microbiology 14,
2023
10.3389/fmicb.2023.1250806
|
URL
Role of Gut Microbiota in Statin-Associated New-Onset Diabetes—a Cross-Sectional and Prospective Analysis of the FINRISK 2002 Cohort
Koponen
K,
Kambur
O,
Joseph
B,
Ruuskanen
M,
Jousilahti
P,
Salido
R,
Brennan
C,
Jain
M,
Meric
G,
Inouye
M,
Lahti
L,
Niiranen
T,
Havulinna
A,
Knight
R &
Salomaa
V.
Arteriosclerosis, Thrombosis, and Vascular Biology
2023
10.1161/ATVBAHA.123.319458
What are patterns of rise and decline?
Raulo
A,
Rojas
A,
Kröger
B,
Laaksonen
A,
Orta
C,
Nurmio
S,
Peltoniemi
M,
Lahti
L &
Žliobaitė
I.
The Royal Society of Open Science 10,
2023
10.1098/rsos.230052
Maternal microbiota communicates with the fetus through microbiota-derived extracellular vesicles
Kaisanlahti
A,
Turunen
J,
Byts
N,
Samoylenko
A,
Bart
G,
Virtanen
N,
Tejesvi
M,
Zhyvolozhnyi
A,
Sarfraz
S,
Kumpula
S,
Hekkala
J,
Salmi
S,
Will
O,
Korvala
J,
Paalanne
N,
Erawijantari
P,
Suokas
M,
Medina
T,
Vainio
S,
Medina
O,
Lahti
L,
Tapiainen
T &
Reunanen
J.
BMC Microbiome 249,
2023
10.1186/s40168-023-01694-9
|
URL
Microbiome-based risk prediction in incident heart failure: A community challenge
Erawijantari
P,
Kartal
E,
Liñares-Blanco
J,
Laajala
T,
Feldman
L,
Challenge
T,
Communities
M,
Carmona-Saez
P,
Shigdel
R,
Marcus
,
Claesson
J,
Bertelsen
R,
Gomez-Cabrero
D,
Minot
S,
Albrecht
J,
Chung
V,
Inouye
M,
Jousilahti
P,
Schultz
J,
Friederich
H,
Knight
R,
Salomaa
V,
Niiranen
T,
Havulinna
A,
Saez-Rodriguez
J,
Levinson
R &
Lahti
L.
medRxiv preprint
2023
10.1101/2023.10.12.23296829
|
URL
Impacts of maternal microbiota and microbial metabolites on fetal intestine, brain, and placenta
Husso
A,
Pessa-Morikawa
T,
Mikael
V,
Kärkkäinen
O,
Kwon
H,
Lahti
L,
Iivanainen
A,
Hanhineva
K &
Niku
M.
BMC Biology(207),
2023
10.1186/s12915-023-01709-9
Advancing microbiome research with machine learning: key findings from the ML4Microbiome COST action
D’Elia
D,
Truu
J,
Lahti
L,
Berland
M,
Papoutsoglou
G,
Ceci
M,
Zomer
A,
Lopes
M,
Ibrahimi
E,
Gruca
A,
Nechyporenko
A,
Frohme
M,
Carrillo-de Santa Pau
T,
Marcos-Zambrano
L,
Hron
K,
Pio
G,
Simeon
A,
Suharoschi
R,
Moreno-Indias
I,
Temko
A,
Nedyalkova
M,
Apostol
E,
Truică
C,
Shigdel
R,
Hasić-Telalović
J,
Bongcam-Rudloff
E,
Przymus
P,
Jordamović
N,
Falquet
L,
Tarazona
S,
Sampri
A,
Isola
G,
Pérez-Serrano
D,
Trajkovik
V,
Klucar
L,
Loncar-Turukalo
T,
Havulinna
A,
Jansen
C &
Claesson
R.
Frontiers in Microbiology 14,
2023
10.3389/fmicb.2023.1257002
Greengenes2 unifies microbial data in a single reference tree
McDonald
D,
Jiang
Y,
Balaban
M,
Cantrell
K,
Zhu
Q,
Gonzalez
A,
Morton
J,
Nicolaou
G,
Parks
D,
Karst
S,
Albertsen
M,
Hugenholtz
P,
DeSantis
T,
Song
S,
Bartko
A,
Havulinna
A,
Jousilahti
P,
Cheng
S,
Inouye
M,
Niiranen
T,
Jain
M,
Salomaa
V,
Lahti
L,
Mirarab
S &
Knight
R.
Nature Biotechnology
2023
10.1038/s41587-023-01845-1
miaSim: an R/Bioconductor package to easily simulate microbial community dynamics
Gao
Y,
Şimşek
Y,
Gheysen
E,
Borman
T,
Li
Y,
Lahti
L,
Faust
K &
Garza
D.
Methods in Ecology and Evolution 14,
2023
10.1111/2041-210X.14129
Infant left amygdala volume is negatively associated with fecal microbiota diversity
Aatsinki
A,
Tuulari
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eBioMedicine
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Acta Diabetologica
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The preterm gut microbiota and administration routes of different probiotics: A randomized controlled trial
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Pediatric research
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The gut microbiome is a significant risk factor for future chronic lung disease
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Impacts of maternal microbiota and microbial metabolites on fetal intestine, brain and placenta
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bioRxiv Cold Spring Harbor Laboratory,
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medRxiv
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10.1101/2022.03.22.22272736
An infancy-onset 20-year dietary counselling intervention and gut microbiota composition in adulthood
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Pietilä
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Nutrients 14(13),
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Can gut microbiota throughout the first 10 years of life predict executive functioning in childhood?
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Gut microbiome composition is predictive of incident type 2 diabetes in a population cohort of 5 572 finnish adults
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Diabetes Care 45(4),
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10.2337/dc21-2358
Efficient computation of Faith’s phylogenetic diversity with applications in characterizing microbiomes
Armstrong
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Zhu
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Impact of combined consumption of fish oil and probiotics on the serum metabolome in pregnant women with overweight or obesity
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EbioMedicine 73,
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Xylo-oligosaccharides in prevention of hepatic steatosis and adipose tissue inflammation: Associating taxonomic and metabolomic patterns in fecal microbiomes with biclustering
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International Journal of Environmental Research and Public Health 18(8),
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Gut microbiota diversity but not composition is related to saliva cortisol stress response at the age of 2.5 months
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F1000Research 10(748),
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Moreno
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Org
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Paciência
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Shigdel
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Stres
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Truu
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Truică
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Frontiers in Microbiology 12,
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Targeting gut microbiota to treat hypertension: A systematic review
Palmu
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International Journal of Environmental Research and Public Health 18(3),
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10.3390/ijerph18031248
Modeling spatial patterns in host-associated microbial communities
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Environmental Microbiology 23(5),
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10.1111/1462-2920.15462
Links between gut microbiome composition and fatty liver disease in a large population sample
Ruuskanen
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Y,
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Tripathi
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Gut Microbes 13,
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Taxonomic signatures of cause-specific mortality risk in human gut microbiome
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Perola
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Nature Communications 12,
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10.1038/s41467-021-22962-y
Gut microbiota of patients with different subtypes of gastric cancer and gastrointestinal stromal tumors
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Gut Pathogens 13,
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Systemic cross-talk between brain, gut, and peripheral tissues in glucose homeostasis: Effects of exercise training (CROSSYS): Exercise training intervention in monozygotic twins discordant for body weight
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BMC Sports Science, Medicine and Rehabilitation 13,
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Early prediction of liver disease using conventional risk factors and gut microbiome-augmented gradient boosting
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Cell Metabolism 34,
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Maternal prenatal psychological distress and hair cortisol levels associate with infant fecal microbiota composition at 2.5 months of age
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Munukka
E,
Uusitupa
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Psychoneuroendocrinology 119,
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Partial restoration of normal intestinal microbiota in morbidly obese women six months after bariatric surgery
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PeerJ – Life & Environment 8,
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Diet, perceived intestinal well-being, fecal microbiota and short chain fatty acids in oat-using subjects with celiac disease or gluten sensitivity.
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Nutrients 12,
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Association between the gut microbiota and blood pressure in a population cohort of 6953 individuals
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Journal of the American Heart Association
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Eicosanoid inflammatory mediators are robustly associated with blood pressure in the general population
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Journal of American Heart Association 9,
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10.1161/JAHA.120.017598
Prebiotic xylo-oligosaccharides targeting faecalibacterium prausnitzii prevent high fat diet-induced hepatic steatosis in rats
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Mäkinen
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Nutrients 12(11),
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10.3390/nu12113225
Gut microbiota and host gene mutations in colorectal cancer patients and controls of iranian and finnish origin
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Anticancer Research 40(3),
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Unsupervised hierarchical clustering identifies a metabolically challenged subgroup of hypertensive individuals
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Journal of Clinical Hypertension 22(9),
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10.1111/jch.13984
Gut microbiota composition is associated with temperament traits in infants
Aatsinki
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Uusitupa
H,
Munukka
E,
Anniina Keskitalo
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O’Mahony
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Brain Behavior and Immunity 80,
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Microbiome data science
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Journal of Biosciences 44,
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10.1007/s12038-019-9930-2
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Microbial communities in a dynamic it in vitro model for the human ileum resemble the human ileal microbiota
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FEMS Microbiology Ecology(8),
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Gut microbiota composition in mid-pregnancy is associated with gestational weight gain but not prepregnancy body mass index
Aatsinki
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Journal of Womens Health
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Signatures of ecological processes in microbial community time series
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Microbiome 6(120),
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Microbial communities as dynamical systems
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Current Opinion in Microbiology 44,
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10.1016/j.mib.2018.07.004
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Stool microbiota composition differs in patients with stomach, colon, and rectal neoplasms
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Karla
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Tikkanen
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Digestive Diseases and Sciences 63(11),
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Comparative gut microbiota and resistome profiling of intensive care patients receiving selective digestive tract decontamination and healthy subjects
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Microbiome 5(1),
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Multi-stability and the origin of microbial community types
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ISME Journal 11,
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Linking statistical and ecological theory: Hubbell’s unified neutral theory of biodiversity as a hierarchical dirichlet process
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Proceedings of the IEEE 105(3),
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Intestinal microbiome landscaping: Insight in community assemblage and implications for microbial modulation strategies
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Vos
W &
Danchin
A.
FEMS Microbiology Reviews 41,
2017
review
10.1093/femsre/fuw045
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PDF
Metagenomics meets time series analysis: Unraveling microbial community dynamics
Faust
K,
Lahti
L,
Gonze
D,
Vos
W &
Raes
J.
Current Opinion in Microbiology 25,
2015
10.1016/j.mib.2015.04.004
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PDF
Fat, fiber and cancer risk in african, americans and rural africans
O’Keefe
S,
Li
J,
Lahti
L,
Ou
J,
Carbonero
F,
Mohammed
K,
Posma
J,
Kinross
J,
Wahl
E,
Ruder
E,
Vipperla
K,
Naidoo
V,
Mtshali
L,
Tims
S,
PGB Puylaert
J,
Krasinskas
A,
Benefiel
A,
Kaseb
H,
Newton
K,
Nicholson
J,
Vos
W,
Gaskins
H &
Zoetendal
E.
Nature Communications 6,
2015
Top science article in Guardian on the release day.
10.1038/ncomms7342
|
PDF
Improved taxonomic assignment of human intestinal 16S rRNA sequences by a dedicated reference database
Ritari
J,
Salojärvi
J,
Lahti
L &
Vos
W.
BMC Genomics 16,
2015
10.1186/s12864-015-2265-y
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PDF
Impact of a wastewater treatment plant on microbial community composition and function in a hyporheic zone of a eutrophic river
Atashgahi
S,
Aydin
R,
Dimitrov
M,
Sipkema
D,
Hamonts
K,
Lahti
L,
Maphosa
F,
Kruse
T,
Saccenti
E,
Dirk Springael
W &
Smidt
H.
Scientific Reports 5(17284),
2015
10.1038/srep17284
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PDF
A novel atlas of gene expression in human skeletal muscle reveals molecular changes associated with aging
Su
J,
Ekman
C,
Oskolkov
N,
Lahti
L,
Ström
K,
Brazma
A,
Groop
L,
Rung
J &
Ola Hansson
.
Skeletal Muscle 5(35),
2015
10.1186/s13395-015-0059-1
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PDF
Binning metagenomic contigs by coverage and composition
Alneberg
J,
Bjarnason
B,
Bruijn
I,
Schirmer
M,
Quick
J,
Ijaz
U,
Lahti
L,
Loman
N,
Andersson
A &
Quince
C.
Nature Methods 11(1144–1146),
2014
CONCOCT algorithm
10.1038/nmeth.3103
|
PDF
Systematic use of computational methods allows stratifying treatment responders in glioblastoma multiforme
Louhimo
R,
Aittomäki
V,
Faisal
A,
Laakso
M,
Chen
P,
Ovaska
K,
Valo
E,
Lahti
L,
Rogojin
V,
Kaski
S &
Hautaniemi.
S.
Systems Biomedicine (special issue) 1,
2014
Critical Assessment of Massive Data Analysis (CAMDA) workshop
10.4161/sysb.28904
|
PDF
Tipping elements in the human intestinal ecosystem
Lahti
L,
Salojärvi
J,
Salonen
A,
Scheffer
M &
Vos
W.
Nature Communications 5,
2014
10.1038/ncomms5344
|
PDF
Impact of diet and individual variation on intestinal microbiota composition and fermentation products in obese men
Salonen
A,
Lahti
L,
Salojärvi
J,
Holtrop
G,
Korpela
K,
Duncan
S,
Date
P,
Johnstone
A,
Lobley
G,
Louis
P,
Flint
H &
Vos
W.
ISME Journal 8,
2014
10.1038/ismej.2014.63
|
PDF
Copy number alterations and neoplasia specific mutations in MELK, PDCD1LG2, TLN1, and PAX5 at 9p in different neoplasias
Sarhadi
V,
Lahti
L,
Scheinin
I,
Ellonen
P,
Kettunen
E,
Serra
M,
Scotlandi
K,
Picci
P &
Knuutila
S.
Genes, Chromosomes and Cancer 53(7),
2014
10.1002/gcc.22168
A fully scalable online pre-processing algorithm for short oligonucleotide microarray atlases
Lahti
L,
Torrente
A,
Elo
L,
Brazma
A &
Rung
J.
Nucleic Acids Research 41(10),
2013
Implementation available through Bioconductor RPA package.
10.1093/nar/gkt229
|
PDF
Associations between the human intestinal microbiota, lactobacillus rhamnosus GG and serum lipids indicated by integrated analysis of high-throughput profiling data
Lahti
L,
Salonen
A,
Kekkonen
R,
Salojärvi
J,
Jalanka-Tuovinen
J,
Palva
A,
Orešič
M &
Vos
W.
PeerJ 1,
2013
Highly accessed, featured in PeerJ journal blog and Top-10 Microbiology collection.
10.7717/peerj.32
|
PDF
Cancer gene prioritization by integrative analysis of mRNA expression and DNA copy number data: A comparative review
Lahti
L,
Schäfer
M,
Klein
H,
Bicciato
S &
Dugas
M.
Briefings in Bioinformatics 14(1),
2013
10.1093/bib/bbs005
|
PDF
Targeted resequencing of 9p in acute lymphoblastic leukemia yields concordant results with array CGH and reveals novel genomic alterations
Sarhadi
V,
Lahti
L,
Scheinin
I,
Tyybäkinoja
A,
Savola
S,
Usvasalo
A,
Räty
R,
Elonen
E,
Ellonen
P,
Saarinen-Pihkala
U &
Knuutila
S.
Genomics 102(3),
2013
10.1016/j.ygeno.2013.01.001
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PDF
Intestinal microbiota, individuality and health. In: Computational methods aiding early-stage drug design (dagstuhl seminar 13212)
Lahti
L
Dagstuhl Reports 3(5) Schloss Dagstuhl–Leibniz-Zentrum fuer Informatik,
2013
10.4230/DagRep.3.5.78
|
URL
The adult intestinal core microbiota is determined by analysis depth and health status
Salonen
A,
Salojärvi
J,
Lahti
L &
Vos
.
Clinical Microbiology and Infection 18(Suppl. 4),
2012
10.1111/j.1469-0691.2012.03855.x
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PDF
MicroRNA profiling predicts survival in anti-EGFR treated chemorefractory metastatic colorectal cancer patients with wild-type KRAS and BRAF
Mosakhani
N,
Lahti
L,
Borze
I,
Karjalainen-Lindsberg
M,
Sundstrom
J,
Ristamaki
R,
Osterlund
P,
Knuutila
S &
Virinder Kaur Sarhadi
.
Cancer Genetics 205(11),
2012
10.1016/j.cancergen.2012.08.003
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PDF
MicroRNA profiling in pediatric acute lymphoblastic leukemia: Novel prognostic tools
Mosakhani
N,
Sarhadi
V,
Usvasalo
A,
Karjalainen-Lindsberg
M,
Lahti
L,
Tuononen
K,
Saarinen-Pihkala
U &
Knuutila
S.
Leukemia & Lymphoma 53(12),
2012
10.3109/10428194.2012.685731
|
PDF
Homozygous deletions of cadherin genes in chondrosarcoma – an array CGH study
Niini
T,
Scheinin
I,
Lahti
L,
Savola
S,
Mertens
F,
Hollmén
J,
Böhling
T,
Kivioja
A,
Nord
K &
Knuutila
S.
Cancer Genetics 205(11),
2012
10.1016/j.cancergen.2012.09.007
MicroRNA microarrays on archive bone marrow core biopsies of leukemias - method validation
Borze
I,
Guled
M,
Musse
S,
Raunio
A,
Elonen
E,
Saarinen-Pihkala
U,
Karjalainen-Lindsberg
M,
Lahti
L &
Knuutila.
S.
Leukemia Research 35,
2011
10.1016/j.leukres.2010.08.005
Biomarker discovery via dependency analysis of multi-view functional genomics data
Faisal
A,
Louhimo
R,
Lahti
L,
Hautaniemi
S &
Kaski
S.
NIPS 2011 workshop from statistical genetics to predictive models in personalized medicine
2011
PDF
Intestinal microbiota in healthy adults: Temporal analysis reveals individual and common core and relation to intestinal symptoms
Jalanka-Tuovinen
J,
Salonen
A,
Nikkilä
J,
Immonen
O,
Kekkonen
R,
Lahti
L,
Palva
A &
Vos
W.
PLoS One 6(7),
2011
PDF
Intcomp: A benchmarking pipeline for integrative cancer gene detection algorithms
Lahti
L,
Schäfer
M,
Klein
H,
Bicciato
S &
Dugas
M.
software,
2011
R-forge
URL
Probabilistic dependency models for data integration in functional genomics
Lahti
L &
Kaski
S.
2011
Machine Learning for Systems Biology workshop, ISMB, Vienna, Austria
PDF
Probabilistic analysis of probe reliability in differential gene expression studies with short oligonucleotide arrays
Lahti
L,
Elo
L,
Aittokallio
T &
Kaski
S.
IEEE/ACM Transactions on Computational Biology and Bioinformatics 8(1) IEEE Computer Society,
2011
10.1109/TCBB.2009.38
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PDF
Array comparative genomic hybridization reveals frequent alterations of G1/s checkpoint genes in undifferentiated pleomorphic sarcoma of bone
Niini
T,
Lahti
L,
Michelacci
F,
Ninomiya
S,
Hattinger
C,
Guled
M,
Böhling
T,
Picci
P,
Serra
M &
Knuutila
S.
Genes, Chromosomes and Cancer 50(5),
2011
10.1002/gcc.20851
|
PDF
Integrative analysis of microRNA, mRNA and aCGH data reveals asbestos- and histology-related changes in lung cancer
Nymark
P,
Guled
M,
Borze
I,
Faisal
A,
Lahti
L,
Salmenkivi
K,
Kettunen
E,
Anttila
S &
Knuutila
S.
Genes, Chromosomes and Cancer 50(8),
2011
10.1002/gcc.20880
|
PDF
Global modeling of transcriptional responses in interaction networks
Lahti
L,
Knuuttila
J &
Kaski
S.
Bioinformatics 26,
2010
R/Matlab implementations available at http://netpro.r-forge.r-project.org/
10.1093/bioinformatics/btq500
|
PDF
Unique microRNA profile in dupuytren’s contracture supports deregulation of beta-catenin pathway
Mosakhani
N,
Guled
M,
Lahti
L,
Borze
I,
Forsman
M,
Ryhänen
J &
Knuutila
S.
Modern Pathology 23,
2010
International Dupuytren Award for best research paper in 2011
10.1038/modpathol.2010.146
|
PDF
CDKN2A, NF2 and JUN are dysregulated among other genes by miRNAs in malignant mesothelioma - a miRNA microarray analysis
Guled
M,
Lahti
L,
Lindholm
P,
Salmenkivi
K,
Bagwan
I,
Nicholson
A &
Knuutila
S.
Genes, Chromosomes and Cancer 48(7),
2009
10.1002/gcc.20669
|
PDF
RPA: Probe reliability and differential gene expression analysis
Lahti
L
software,
2009
R/Bioconductor: RPA
10.18129/B9.BIOC.RPA
|
URL
A brief overview on the BioPAX and SBML standards
Lahti
L
arXiv,
2007
(in Finnish)
URL
Gene expression profiles in asbestos-exposed epithelial and mesothelial lung cell lines
Nymark
P,
Lindholm
P,
Korpela
M,
Lahti
L,
Ruosaari
S,
Kaski
S,
Hollmen
J,
Anttila
S,
Kinnula
V &
Knuutila
S.
BMC Genomics 8(62),
2007
10.1186/1471-2164-8-62
Integrating probe-level expression changes across generations of affymetrix arrays
Elo
L,
Lahti
L,
Skottman
H,
Kyläniemi
M,
Lahesmaa
R &
Aittokallio
T.
Nucleic Acids Research 33(22),
2005
10.1093/nar/gni193
|
PDF
Associative clustering by maximizing a Bayes factor
Sinkkonen
J,
Nikkilä
J,
Lahti
L &
Kaski
S.
Helsinki University of Technology and Laboratory of Computer and Information Science,
2003
PDF