Bioinformatics
Welcome to the Bioinformatics Research Page! Here we have listed all of our faculty, publications, and labs that are associated with the Bioinformatics Field.
Labs
Scientific Leader: Dr. Andrew Christlieb
There are three categories of applications our group considers. The first is related to modeling complex multi physics problems in plasma science. The second area we work on is the development of methods that are aimed at solving interface problems in polymer membranes; think fuel cells, solar cells and batteries. The third area we work on is the development of ultra fast methods (sub-linear methods) for identification of sparse signals.
Scientific Leader: Dr. John Verboncoeur
Theoretical and computational plasma physics, with a broad range of applications spanning from low temperature plasmas for lighting, thrusters and materials processing to hot plasmas for fusion; from ultra-cold plasmas to particle accelerators; from beams to pulsed power; and from intense kinetic nonequilibrium plasmas to high power microwaves.
Scientific Leader: Dr. Michael Murillo
Our group is involved in the two seemingly disparate research directions of computational plasma physics and agent-based modeling. In both cases, we employ computational methods for interacting many-body systems to understand the collective dynamics of the systems we study.
Scientific Leader: Dr. Min Chen
MSU Computational Seismology Lab works on analyzing, numerical modeling, and full waveform inversion of seismic array data from various sources, such as earthquakes, explosions, and ambient noise sources. Our goal is to better understand dynamic processes of the Earth on different time and spatial scales.
Scientific Leader: Dr. Arjun Krishnan
The Krishnan lab develops genomics/computational approaches to gain more nuanced and accurate insights into how our genome relates to health and disease. Combining statistics/machine-learning with large-scale genomic/clinical data, we build models and predictions about the genetic basis of biomedical phenomena, especially in an age-, sex-, and tissue-specific manner. Our overarching goal is to use these methods and insights to transform our ability to link an individual's genomic profiles to her/his physiological traits, disease risks, and clinical outcomes.
Scientific Leader: Dr. Matthew Hirn
The CEDAR team works at the interface of harmonic analysis and machine learning. We develop tools that uncover complex, multiscale patterns in high dimensional data by considering the underlying data geometries, invariants, hierarchies and statistics. Our focus is on rigorous mathematical theory coupled with state of the art numerical results in application specific domains. Research areas include:
- Wavelet theory and deep learning (scattering transforms)
- Diffusion based manifold learning
- Smooth (Whitney) extensions and interpolations of data
- Many body problems in quantum chemistry
- Analysis of bio-medical data
Scientific Leader: Dr Alex Dickson
Pharmacological biophysics / Network modeling / Rare event sampling methods
Publications
Faculty member Tony Gao gets paper published on the cover of current issue of Physical Review Letters.
The Murillo Group has recently released a new paper published by The Journal of Statistical Physics on August, 2017 about Conservative, Entropic Multispecies BGK Model.
Link: https://link.springer.com/article/10.1007/s10955-017-1824-9
Cornell Universiry Library published a paper by faculty member Matthew J. Hirn on 15 August, 2016.
CMSE researchers Gautham Dharuman & Michael Murillo have a new paper published by The Journal of Chemical Physics for their work involving Ewald method and medium-range interactions for charged-particle systems.
Multiscale Modeling and Simulation has published the following paper by Matthew Hirn, Stephane Mallat, & Nicolas Poilvert for their work in Wavelet Scattering on 2 May 2017.
The Biophysical Journal had published a paper by Alex Dickson & Samual D. Lotz, published on 28 February 2017 for their work on Ligand Pathways.
Link: http://www.sciencedirect.com/science/article/pii/S0006349517300450
Current Topics in Medicinal Chemistry featured a new paper by Alex Dickson, Pratyush Tiwary, & Harish Vashisth on 14 April 2017 for their work in Kinetics of Ligand Binding.
The Journal of Computational Chemistry featured a new paper by Alex Dickson, Christopher T. Bailey, & John Karanicolas, on 5 June 2017.
Link: http://onlinelibrary.wiley.com/doi/10.1002/jcc.24517/full
Xianfeng Hu, Mark Iwen, & Hyejin Kim authored a new paper for their work in Rapid Computing published by Numer. Algor. (2017) 74: 1029.
DOI: 10.1007/s11075-016-0184-x
Link: http://users.math.msu.edu/users/markiwen/Papers/Legendre_SUBMITTED.pdf
Ariel Herbert-Voss, Matthew J. Hirn, & Frederick McCollum published a paper in Revista Mathematica Iberoamericana for their work on Computing Minimal Interpolants.
Link: http://www.ems-ph.org/journals/show_abstract.php?issn=0213-2230&vol=33&iss=1&rank=2
The Murillo Group has released a new paper published by Physical Review E on April 10th, 2017 about Hydrogen Plasmas within the Coupled-mode Regime.
Link: https://journals.aps.org/pre/abstract/10.1103/PhysRevE.95.043202
M. S. Murillo & M. Marciante published a new paper on Thermodynamic and Kinetic Properties in Phys. Rev. Lett. 118, 025001 – 10 January 2017
Link: https://doi.org/10.1103/PhysRevLett.118.025001
Alex Dickson & Samuel D Lotz published a new paper for their work in Ligand Pathways on 26 May 2016. in J. Phys. Chem. B
DOI: 10.1021/acs.jpcb.6b04012