Ramgopal R Mettu

Tulane University | TU · Department of Computer Science

Antigen conformation shapes CD4+ T-cell specificity through mechanisms of antigen processing, and the consequences for immunity may rival those from conformational effects on antibody specificity. CD4+ T cells initiate and control immunity to pathogens and cancer and are at least partly responsible for immunopathology associated with infection, aut...

Additive manufacturing has emerged as a next-generation technology for advanced fabrication. Fused Filament Fabrication (FFF) is the most widespread form of material extrusion additive manufacturing and has growing applications in large scale construction. Despite its advantages, FFF is limited by structural weaknesses introduced by cooling of the...

Antigen processing in the class II MHC pathway depends on conventional proteolytic enzymes, potentially acting on antigens in native-like conformational states. CD4+ epitope dominance arises from a competition among antigen folding, proteolysis, and MHCII binding. Protease-sensitive sites, linear antibody epitopes, and CD4+ T-cell epitopes were map...

We present a new algorithm for coordinating the motion of multiple extruders to increase throughput in fused filament fabrication (FFF)/fused deposition modelling (FDM) additive manufacturing. Platforms based on FFF are commonly available and advantageous to several industries, but are limited by slow fabrication time and could be could be signific...

We present a new algorithm for coordinating the motion of multiple extruders to increase throughput in fused filament fabrication (FFF)/fused deposition modelling (FDM) additive manufacturing. Platforms based on FFF are commonly available and advantageous to several industries, but are limited by slow fabrication time and could be could be signific...

Chicken ovalbumin (cOVA) has been studied for decades primarily due to the robust genetic and molecular resources that are available for experimental investigations. cOVA is a member of the serpin superfamily of proteins that function as protease inhibitors, although cOVA does not exhibit this activity. As a serpin, cOVA possesses a protease-sensit...

The importance of CD4+ T helper (Th) cells is well appreciated in view of their essential role in the elicitation of antibody and cytotoxic T cell responses. However, the mechanisms that determine the selection of immunodominant epitopes within complex protein antigens remain elusive. Here, we used ex vivo stimulation of memory T cells and screenin...

Antigen processing in the class II MHC pathway depends on conventional proteolytic enzymes, potentially acting on antigens in native-like conformational states. CD4+ epitope dominance arises from a competition between antigen folding, proteolysis, and MHCII binding. Protease-sensitive sites, linear antibody epitopes, and CD4+ T-cell epitopes were m...

We propose a decentralised variant of Monte Carlo tree search (MCTS) that is suitable for a variety of tasks in multi-robot active perception. Our algorithm allows each robot to optimise its own individual action space by maintaining a probability distribution over plans in the joint-action space. Robots periodically communicate a compressed form o...

Potent antibody responses depend on the proteolytic processing of protein antigens and the presentation of MHC Class II bound peptides to CD4+ T cells. We have previously reported a single amino acid substitution (R494A) made to pseudomonas exotoxin A domain III (PE-III) that alters processing and antibody responses with only minor changes to CD4+...

The most widely used methods for toolpath planning in fused deposition 3D printing slice the input model into successive 2D layers in order to construct the toolpath. Unfortunately slicing-based methods can incur a substantial amount of wasted motion (i.e., the extruder is moving while not printing), particularly when features of the model are spat...

Effective adaptive immune responses depend on activation of CD4+ T cells via the presentation of antigen peptides in the context of major histocompatibility complex (MHC) class II. The structure of an antigen strongly influences its processing within the endolysosome and potentially controls the identity of peptides that are presented to T cells. A...

We present an algorithm for selecting when to communicate during online planning phases of coordinated multi-robot missions. The key idea is that a robot decides to request communication from another robot by reasoning over the predicted information value of communication messages over a sliding time-horizon, where communication messages are probab...

We propose a decentralized variant of Monte Carlo tree search (MCTS) that is suitable for a variety of tasks in multi-robot active perception. Our algorithm allows each robot to optimize its own actions by maintaining a probability distribution over plans in the joint-action space. Robots periodically communicate a compressed form of their search t...

A meta-analysis of CD4+ T cell epitope maps reveals clusters and gaps in envelope-protein (E protein) immunogenicity that can be explained by the likelihood of epitope processing, as determined by E protein three-dimensional structures. Differential processing may be at least partially responsible for variations in disease severity among arbo-flavi...

We propose a decentralised variant of Monte Carlo tree search (MCTS) that is suitable for a variety of tasks in multi-robot active perception. Our algorithm allows each robot to optimise its own individual action space by maintaining a probability distribution over plans in the joint-action space. Robots periodically communicate a compressed form o...

T-cell CD4+ epitopes are important targets of immunity against infectious diseases and cancer. State-of-the-art methods for MHC class II epitope prediction rely on supervised learning methods in which an implicit or explicit model of sequence specificity is constructed using a training set of peptides with experimentally tested MHC class II binding...

Unlabelled: Helper T-cell epitope dominance in human immunodeficiency virus type 1 (HIV-1) envelope glycoprotein gp120 is not adequately explained by peptide binding to major histocompatibility complex (MHC) proteins. Antigen processing potentially influences epitope dominance, but few, if any, studies have attempted to reconcile the influences of...

Structure determination from X-ray crystallography requires numerous stages of iterative refinement between real and reciprocal space. Current methods that fit a model structure to X-ray data therefore utilize a refined experimental electron density map along with a scoring function that characterizes the fit of the density map to structure. Additi...

Clustering is a fundamental problem in unsupervised learning, and has been studied widely both as a problem of learning mixture models and as an optimization problem. In this paper, we study clustering with respect the emph{k-median} objective function, a natural formulation of clustering in which we attempt to minimize the average distance to clus...

Many algorithms and applications involve repeatedly solving variations of the same inference problem; for example we may want to introduce new evidence to the model or perform updates to conditional dependencies. The goal of adaptive inference is to take advantage of what is preserved in the model and perform inference more rapidly than from scratc...

In this article we describe a computational method that automatically generates chemically relevant compound ideas from an initial molecule, closely integrated with in silico models, and a probabilistic scoring algorithm to highlight the compound ideas most likely to satisfy a user-defined profile of required properties. The new compound ideas are...

One of the defining challenges of drug discovery is the need to make complex decisions regarding the design and selection of potential drug molecules based on a relative scarcity of experimental data.

Dual-decomposition (DD) methods are quickly becoming important tools for estimating the minimum energy state of a graphical model. DD methods decompose a complex model into a collection of simpler subproblems that can be solved exactly (such as trees), that in combination provide upper and lower bounds on the exact solution. Subproblem choice can p...

Many algorithms and applications involve repeatedly solving variations of the same inference problem, for example to introduce new evidence to the model or to change conditional dependencies. As the model is updated, the goal of adaptive inference is to take advantage of previously computed quantities to perform inference more rapidly than from scr...

Dual-decomposition (DD) methods are quickly becoming important tools for estimating the minimum energy state of a graphical model. DD methods decompose a complex model into a collection of simpler subproblems that can be solved exactly (such as trees), that in combination provide upper and lower bounds on the exact solution. Subproblem choice can p...

Not available Computer Sciences

We propose a method of hidden structure learning using a log-linear model of grammar. We apply this to learning over multiple possible underlying representations. We achieve good results for learning Tesar’s (2006) Paka languages. With a simple Markedness> Faithfulness bias, we obtain generalized patterns which make single abstract underlying repre...

Mass spectrometry is one of the main tools for protein identification in complex mixtures. When the sequence of the protein is known, we can check to see if the known mass distribution of peptides for a given protein is present in the recorded mass distribution of the mixture being analyzed. Unfortunately, this general approach suffers from high fa...

Many applications involve repeatedly computing the optimal, maximum a posteriori (MAP) configuration of a graphical model as the model changes, often slowly or incrementally over time, e.g., due to input from a user. Small changes to the model often require updating only a small fraction of the MAP configuration, suggesting the possibility of perfo...

In this paper, we investigate the problem of scheduling flows for fair stream allocation (or, stream scheduling) in ad hoc networks in which the transmitter and receiver use multiple antennas called Multiple Input Multiple Output (MIMO) technology. Our main contributions include: i) the concept of stream allocation to flows based on their traffic d...

Many algorithms and applications involve re- peatedly solving variations of the same inference problem; for example we may want to introduce new evidence to the model or perform updates to conditional dependencies. The goal of adap- tive inference is to take advantage of what is pre- served in the model and perform inference more rapidly than from...

To reap the benefits of advances in wireless technologies as well as provide backward compatibility with current investments, future wireless routers that constitute the backbone of Wireless Mesh Networks (WMNs) will be equipped with multiple radios of different technology standards. The multiplicity of channels, radios and technology standards mak...

In this paper, we investigate the problem of scheduling flows for fair stream allocation in ad hoc networks utilizing multiple antennas at the transmitter and receiver side known as Multiple Input Multiple Output (MIMO) antenna technology. Our main contributions include: i) the concept of stream allocation to flows based on their traffic demands or...

We describe an efficient algorithm for protein backbone structure determination from solution Nuclear Magnetic Resonance (NMR) data. A key feature of our algorithm is that it finds the conformation and orientation of secondary structure elements as well as the global fold in polynomial time. This is the first polynomial-time algorithm for de novo h...

We cast the problem of identifying protein-protein interfaces, using only unassigned NMR spectra, into a geometric clustering problem. Identifying protein-protein interfaces is critical to understanding inter- and intra-cellular communication, and NMR allows the study of protein interaction in solution. However it is often the case that NMR studies...

Our paper describes the first provably-efficient algorithm for determining protein structures de novo, solely from experimental data. We show how the global nature of a certain kind of NMR data provides quantifiable complexity-theoretic benefits, allowing us to classify our algorithm as running in polynomial time. While our algorithm uses NMR data...

Clustering is a fundamental problem in unsupervised learning, and has been studied widely both as a problem of learning mixture models and as an optimization problem. In this paper, we study clustering with respect to the k-median objective function, a natural formulation of clustering in which we attempt to minimize the average distance to cluster...

We have developed a novel algorithm for protein backbone structure determination using global orientational restraints on internuclear bond vectors derived from residual dipolar couplings (RDCs) measured in solution NMR. The algorithm is a depth-first search (DPS) strategy that is built upon two low-degree polynomial equations for computing the bac...

vi List of Figures xi Chapter 1

We introduce a natural variant of the (metric uncapacitated) k-median problem that we call the online median problem. Whereas the k-median problem involves optimizing the simultaneous placement of k facilities, the online median problem imposes the following additional constraints: the facilities are placed one at a time; a facility, once placed, c...

. We describe our implementation of an algorithm to maintain the connected components and the biconnected components of a graph where vertex and edge insertions are allowed. Algorithms for this problem can be applied to task decomposition in engineering design. Connected components are maintained using a disjoint set data structure and the biconnec...

. We consider an algorithm to maintain the connected components and the biconnected components of a graph where vertex and edge insertions are allowed. Algorithms for this problem can be applied to task decomposition in engineering design. Connected components are maintained using a disjoint set data structure and the biconnected components are mai...