ABOUT THE LAB
We are a Computational Biology lab dedicated to analyzing multiple types of biomedical data to gain insight on brain development and brain disorders.
We are at the Lieber Institute for Brain Development.
RESEARCH
The Lieber Institute for Brain Development
The mission of the Lieber Institute for Brain Development is to translate the understanding of basic genetic and molecular mechanisms of schizophrenia and related developmental brain disorders into clinical advances that change the lives of affected individuals. The LIBD has the largest, most carefully curated and characterized collection of brains for the study of developmental brain disorders in the world, and generates large related datasets on genotype, gene expression, epigenomics, brain imaging, behavior and medical records. Our group is focused on analyzing these data in collaboration with other LIBD scientists.
Brain genomics, data integration and machine learning
The genome is a complex place with multiple different contexts and relationships between them. One of our goals is to develop new analytical approaches combining graph theory and machine learning to explore the genome in novel ways and find links between genomic context and phenotypes.
Brain Somatic Mosaicism
Somatic mosaicism refers to the fact that cells within an organism have different genomes. Several studies have shown that somatic mosaicism occurs in all brains and that somatic mutations in a subset of cells can cause various rare neurodevelopmental disorders. However, for most individuals, the extent and consequences of somatic mosaicism are largely unknown. The complexity and unique features of the brain suggest that somatic mosaicism can play an important role in behavior and cognition. As part of the NIMH-funded Brain Somatic Mosaicism Network, we work on identifying somatic genomic variants in the brain, the genomic features they are associated to, and how they relate to Schizophrenia and other brain disorders.
Collaborative and reproducible data analysis
We believe that data analysis is better when done collaboratively. One of our projects is a minimalist by design and easy to adopt system to build and share reproducible data analysis workflows. Check it out on github.
PUBLICATIONS
Erwin, JA*, Paquola, AC*,
Singer, T, Gallina, I, Novotny, M, Quayle, C, Bedrosian,
T, Butcher, CR, Herdy, JR, Lasken,
RS, Muotri, AR, Gage, FH. L1-Associated
Genomic Regions are Deleted in Somatic Cells of the Healthy Human Brain. Nature Neuroscience. 2016. doi:
10.1038/nn.4388. (* equal
contribution)
Paquola,
AC,
Erwin, JA, Gage, FH A framework for collaborative
computational research. bioRxiv
2015; 033654
Paquola, ACM*, Erwin, JA*, Gage, FH, Insights into the role of
somatic mosaicism in the brain. Current
Opinion in Systems Biology. 2017. (* equal contribution)
McConnell, MJ*, Moran, JV*, Abyzov, Akbarian, S, Bae, T, Erwin, JA, Fasching,
L, Flasch, DA, Freed, D, Ganz, J, Kwan, KY, Kwon1,M, Lodato, MA, Paquola,
ACM, Rodin, R, Rosenbluh, C, Sestan,
N, Sherman, MA, Song, S, Straub, R, Thorpe, J, Weinberger, DR, Urban, AE, Gage,
FH, Lehner, T, Senthil, G,
Walsh, C, Chess, A, Courchesne, E, Gleeson, JG, Kidd,
JM, Park, PJ, Pevsner, J, Vaccarino, FM, Brain
Somatic Mosaicism Network. Intersection of Diverse Neuronal Genomes and
Neurological Disease: The Brain Somatic Mosaicism Network. Science. 2017.
Lacar, B, Linker, S, Jaeger, B, Krishnaswami,
S, Barron, J, Kelder, M, Parylak,
S, Paquola, AC, Venepally, P, Novotny, M,
O'Connor, C, Fitzpatrick, C, Erwin, JA, Hsu, J, Husband, J, McConnell, MJ, Lasken, R, and Gage, FH. Nuclear RNA-seq
of single neurons reveals molecular signatures of activation. Nature Communications. 7:12020.
Vadodaria KC, Mertens
J, Paquola AC, Bardy C, Li X, Jappelli R, Fung L, Marchetto MC,
Hamm M, Gorris M, Koch P, Gage FH. Generation of
functional human serotonergic neurons from fibroblasts. Mol Psychiatry. 2016 Jan;21(1):49-61.
Mertens J, Paquola AC, Ku M, Hatch E, Bhnke L, Ladjevardi S, McGrath
S, Campbell B, Lee H, Herdy JR, Gonalves
JT, Toda T, Kim Y, Winkler J, Yao J, Hetzer MW, Gage
FH. Directly Reprogrammed Human Neurons Retain Aging-Associated Transcriptomic
Signatures and Reveal Age-Related Nucleocytoplasmic Defects. Cell
Stem Cell. 2015 Dec
3;17(6):705-18.
Marchetto MC, Narvaiza
I, Denli AM, Benner C, Lazzarini
TA, Nathanson JL, Paquola AC, Desai KN, Herai RH, Weitzman MD, Yeo GW, Muotri
AR, Gage FH. Differential L1 regulation in pluripotent stem cells of humans and
apes. Nature. 2013 Nov 28;503(7477):525-9.
Lima
WC, Paquola AC, Varani AM, Van Sluys MA, Menck CF. Laterally transferred genomic
islands in Xanthomonadales related to pathogenicity
and primary metabolism. FEMS Microbiol Lett. 2008 Apr;281(1):87-97.
da
Rocha RP, Paquola AC, Marques Mdo V, Menck CF, Galhardo RS.
Characterization of the SOS regulon of Caulobacter crescentus. J Bacteriol. 2008 Feb;190(4):1209-18.
Ojopi EP, Oliveira PS, Nunes DN, Paquola
AC, DeMarco R, Gregrio SP, Aires KA, Menck
CF, Leite LC, Verjovski-Almeida
S, Dias-Neto E. A quantitative view of the transcriptome
of Schistosoma mansoni adult-worms using SAGE. BMC Genomics. 2007 Jun 21;8:186.
Reis
EM, Ojopi EP, Alberto FL, Rahal P, Tsukumo F, Mancini UM, Guimares
GS, Thompson GM, Camacho C, Miracca E, Carvalho AL, Machado AA, Paquola AC, Cerutti JM, da Silva AM, Pereira GG, Valentini
SR, Nagai MA, Kowalski LP, Verjovski-Almeida S, Tajara EH, Dias-Neto E, Bengtson MH, Canevari RA, Carazzolle MF, Colin C, Costa FF, Costa MC, Estcio MR, Esteves LI, Federico
MH, Guimares PE, Hackel C,
Kimura ET, Leoni SG, Maciel RM, Maistro
S, Mangone FR, Massirer KB,
Matsuo SE, Nobrega FG, Nbrega
MP, Nunes DN, Nunes F, Pandolfi JR, Pardini MI, Pasini FS, Peres T, Rainho CA,
dos Reis PP, Rodrigus-Lisoni FC, Rogatto
SR, dos Santos A, dos Santos PC, Sogayar MC, Zanelli
CF; Head and Neck Annotation Consortium. Large-scale transcriptome analyses
reveal new genetic marker candidates of head, neck, and thyroid cancer. Cancer Res. 2005 Mar 1;65(5):1693-9.
da
Costa RM, Riou L, Paquola AC, Menck CF, Sarasin A. Transcriptional profiles of unirradiated
or UV-irradiated human cells expressing either the cancer-prone XPB/CS allele
or the noncancer-prone XPB/TTD allele. Oncogene. 2005 Feb 17;24(8):1359-74.
Reis
EM, Nakaya HI, Louro R, Canavez FC, Flatschart AV,
Almeida GT, Egidio CM, Paquola AC, Machado AA,
Festa F, Yamamoto D, Alvarenga
R, da Silva CC, Brito GC, Simon SD, Moreira-Filho CA, Leite KR, Camara-Lopes LH, Campos FS, Gimba
E, Vignal GM, El-Dorry H, Sogayar MC, Barcinski MA, da
Silva AM, Verjovski-Almeida S. Antisense intronic non-coding RNA levels correlate to the degree of
tumor differentiation in prostate cancer. Oncogene.
2004 Aug 26;23(39):6684-92.
Louro R, Nakaya HI, Paquola AC,
Martins EA, da Silva AM, Verjovski-Almeida S, Reis
EM. RASL11A, member of a novel small monomeric GTPase
gene family, is down-regulated in prostate tumors. Biochem Biophys Res Commun.
2004 Apr 9;316(3):618-27.
Brentani
H, et al., Paquola AC, et al., Zalcberg H;
Human Cancer Genome Project/Cancer Genome Anatomy Project Annotation
Consortium; Human Cancer Genome Project Sequencing Consortium. The generation
and utilization of a cancer-oriented representation of the human transcriptome
by using expressed sequence tags. Proc Natl Acad Sci U S A. 2003 Nov 11;100(23):13418-23. Epub 2003 Oct 30.
Verjovski-Almeida S, DeMarco R, Martins EA, Guimares PE, Ojopi EP, Paquola
AC, Piazza JP, Nishiyama MY Jr, Kitajima JP, Adamson RE, Ashton PD, Bonaldo
MF, Coulson PS, Dillon GP, Farias LP, Gregorio SP, Ho PL, Leite
RA, Malaquias LC, Marques RC, Miyasato
PA, Nascimento AL, Ohlweiler
FP, Reis EM, Ribeiro MA, S RG, Stukart
GC, Soares MB, Gargioni C,
Kawano T, Rodrigues V, Madeira AM, Wilson RA, Menck CF,
Setubal JC, Leite LC, Dias-Neto
E. Transcriptome analysis of the acoelomate human parasite Schistosoma mansoni. Nat Genet. 2003 Oct;35(2):148-57. Epub 2003 Sep
14.
Paquola
AC,
Nishyiama MY Jr, Reis EM, da Silva AM, Verjovski-Almeida S. ESTWeb:
bioinformatics services for EST sequencing projects. Bioinformatics. 2003 Aug
12;19(12):1587-8.
Paquola
AC,
Machado AA, Reis EM, Da Silva AM, Verjovski-Almeida
S. Zerg: a very fast BLAST parser library.
Bioinformatics. 2003 May 22;19(8):1035-6.
OPEN POSITIONS
Data Scientist
As a Data Scientist, your role is to develop data analysis workflows, machine learning models, databases and visualizations, with main focus on genomics. You will work together with scientists of many different backgrounds and fields of expertise and will contribute to the writing of papers and grants.
Qualifications:
- Master’s or Bachelor’s degree in computer science, bioinformatics, mathematics, physics or related area.
- Proficiency in Python, machine learning and databases.
- Excellent analytical and problem solving skills.
- Excellent verbal and written communication skills.
Job type: full-time.
Job location: Baltimore, MD.
To apply: please email your CV to apua.paquola@libd.org
CONTACT
The Lieber Institute for Brain Development
855 North Wolfe Street
Suite 300, 3rd Floor
Baltimore, MD 21205
email: apua.paquola@libd.org