Starting August 2015 I move to Urbana, U Illinois where I will be a Professor
of Bioengineering and Bliss Faculty Scholar at the University of Illinois
Urbana-Champaign (UIUC) with appointments at Carl Woese Institute of Genome
Biology and National Center for Supercomputing Applications
will maintain a joint appointment at Department of Biological and
Environmental Sciences at Brookhaven National Laboratory
on Long Island, New York.
My publication/citation record
from the ISI Web of Science can be found by following this link:
(roll over the icon for a quick
The detailed scientific track
record is in my Curriculum Vitae which I am trying to keep up to date.
To quickly search for my recent preprints on arxiv.org
you can follow
this link. Keep
in mind, however, that some
of my recent papers didn't make it to the arxiv.
The members of my research group are listed here.
Department of Biology, Brookhaven National Laboratory, Upton, New York,
Tel: +1-(631) 327-8222 (cell)
E@mail: ssmaslov at gmail.com
My recent Picasa albums can be found here.
Some older photos are stored here.
current research is focused on computational systems biology. My collaborators
and I analyzed large-scale experimental datasets and developed predictive
models which are fundamentally important for a host of applications including
Big Data, biomedicine, metabolic engineering for biofuels, emerging "omics"
technologies, and synthetic biology. Below I highlight the findings from some
of my published and submitted articles:
my collaborators and I proposed general edge rewiring algorithms allowing
one to detect and visualize statistically significant topological patterns
in large networks. We applied them to yeast PPI and regulatory networks to
demonstrate that hubs in these networks rarely directly interact with each
other. Our algorithms are currently used and cited to analyze both
biomolecular as well as neuroscience (connectome, fMRI) networks.
(Nucleic Acids Research 2005)
we demonstrated that self-interacting proteins forming homodimers (or
homooligomers) are overrepresented in PPI networks and have larger than
average degrees. Our observations are important for understanding functional, structural, and evolutionary properties of protein-protein
In (PNAS 2007)
we proposed and simulated a genome-scale mass action model of the PPI
network in baker's yeast taking into account experimentally determined
protein concentrations, subcellular localizations, homo- and hetero-dimers
and multi-protein complexes. This predictive model allowed us to quantify
the cascading effects of changes in protein concentrations affecting
stability of mass action steady state of genome-wide PPI networks.
Variants of this model are relevant for cancer
biology in understanding the control of apoptosis by Bcl-2 family
of proteins and for biomedical
applications of gene regulation by microRNA/ceRNA.
In (PRL 2008),
2011), and (PLoS
Comp Bio 2013) we
quantified the effects of, respectively, fluctuations in concentrations,
non-specific interactions, and structural stability of proteins on
genome-wide mass action dynamics of PPI networks.
my collaborators and I proposed the "toolbox" model of
co-evolution of metabolic and regulatory networks by Horizontal Gene
Transfer (HGT) in bacterial and archaeal genomes. Our model explained a
number of trends in properties of these networks with genome size. These
insights into modular properties of bacterial genomes and networks are
important for bioengineering and biomedical applications.
(PLoS Comb Bio 2011)
we extended our toolbox model to include anabolic (biosynthetic) pathways.
To this end we came up with a computational algorithm predicting the
minimal biosynthetic pathway to add to the existing metabolic network of
an organism so that it can synthesize a desired target metabolite.
Algorithms proposed in this paper are relevant for synthetic biology applications.
In (NAR 2011;
2013) we identified
functional and evolutionary determinants of sizes of gene families and the
frequency with which they are encoded in bacterial genomes. We plan to
repeat this analysis on a much larger dataset of ~1018 pairwise
comparisons of protein-coding genes in 30,000 sequenced genomes and ~200
metagenomes in the Big Data in
2009 (journal cover);
PNAS 2015) we
developed scalable computational algorithms for deriving the basic genome
- the consensus genome sequence of a bacterial species excluding variable
segments and idiosyncratic genome rearrangements. Basic genome is
essential for working with Big
Data in bacterial genomics.
developed a suite of computational methods for analyzing Single-Nucleotide
Polymorphisms (SNP) within this basic genome and separating vertically
inherited, clonal segments from recombined (horizontally transferred)
ones. For closely related pairs of E. coli strains, we identified a
patchwork of long (10s to 100s kb) recombined segments interspersed among
clonally inherited genomic segments. Once sequence divergence between
strains exceeds ~1.3% clonal segments virtually disappear. Our
implicate generalized transducing phages in horizontal transfer of genomic
segments between strains and suggest their importance in defining the
boundaries of bacterial species. Biomedical
applications of our findings include understanding the emergence
and spread of pathogenic bacterial strains (e.g. E. coli) and of antibiotic
resistance in bacterial populations.
Reports, 2015) we identified the optimal ("well-tempered")
strategy for lytic-lysogenic transition by phages in fluctuating
environments subject to episodic collapses. In (PLoS
Comp Bio 2015) we modeled the dynamics of population waves of bacteria
triggered by local extinctions of dominant populations e.g. caused by
phage predation. Our models are relevant for the analysis of metagenomics
data and for bioenergy
applications such as e.g. preventing phage infections in
2015) we presented a general theoretical and numerical analysis of the
problem of spontaneous emergence of autocatalysis for polymers capable of
template-assisted ligation driven by cyclic changes in the environment.
Our central result is the existence of the first order transition between
the regime dominated by free monomers and that with a self-sustaining
population of sufficiently long oligomers. Another key result is the
emergence of the kinetically limited optimal overlap length between a
template and its two substrates.
DOE Systems Biology Knowledgebase
I am a co-PI of Department of Energy Systems Biology Knowledgebase project
(KBase), where I lead a team of scientists
from BNL and Cold Spring Harbor Laboratory. In addition to
Brookhaven KBase project involves scientists from 3 other national labs:
Lawrence Berkeley, Argonne, and Oak Ridge, and from several universities.
KBase is a software and data environment designed to enable researchers to
collaboratively generate, test and share new hypotheses about gene and protein
functions, perform large-scale analyses on a scalable computing
infrastructure, and model interactions in microbes, plants, and their
communities. KBase provides an open, extensible framework for secure sharing
of data, tools, and scientific conclusions in predictive and systems biology
I am also
interested in emergent properties of large information
networks. These networks connect routers in the Internet, link
webpages, or scientific publications to each other, etc.
My recent research on information networks focused on the following topics:
In my studies I
often (but not always) use the tools of theoretical statistical physics.
Even more important than tools, physics taught me the power of simple models
in revealing the essence of complex phenomena. Simple
models are indispensable if one wants not just to reproduce the complexity of
a system (e.g. by a detailed computer simulations) but to truly understand
Before concentrating on complex
networks I worked on a variety of topics including (in reverse chronological
order) Econophysics, Low-dimensional
magnetism, and Self-Organized Criticality.