Manish P. Kurhekar

Genome-wide pathway analysis and visualization using gene expression data.

Visualization of results for high performance computing pose special problems due to the complexity and the volume of data these systems manipulate. We present an approach for visualization of c-DNA microarray gene expression data in metabolic and regulatory pathways using multi-resolution animation at different levels of detail. We describe three scoring functions to characterize pathways at the transcriptional level based on gene expression, coregulation and cascade effect. We also assess the significance of each pathway score on the basis of their biological connotation.

A system for knowledge management in bioinformatics

The emerging biochip technology has made it possible to simultaneously study expression (activity level) of thousands of genes or proteins in a single experiment in the laboratory. However, in order to extract relevant biological knowledge from the biochip experimental data, it is critical not only to analyze the experimental data, but also to cross-reference and correlate these large volumes of data with information available in external biological databases accessible online. We address this problem in a comprehensive system for knowledge management in bioinformatics called e2e. To the biologist or biological applications, e2e exposes a common semantic view of inter-relationship among biological concepts in the form of an XML representation called eXpressML, while internally, it can use any data integration solution to retrieve data and return results corresponding to the semantic view. We have implemented an e2e prototype that enables a biologist to analyze her gene expression data in GEML or from a public site like Stanford, and discover knowledge through operations like querying on relevant annotated data represented in eXpressML using pathways data from KEGG, publication data from Medline and protein data from SWISS-PROT.

Economically Efficient Virtualization over Cloud Using Docker Containers

In computing era, a virtual version of a stratagem or resource, such as computer network resources, server, storage device, or a combination of these usually refers as virtualization where the framework segregates the resources into one or more execution instances. A Virtual Machine (VM) created on the host hardware as a software is called a hypervisor or a VM manager. Nowadays, hypervisor based virtualization is the most prevailing technology for virtual environment. It is supple and performs for equivalently any guest operating system (OS) but it leads to overload on memory and CPU. Nevertheless, container based virtualization (or OS virtualization) technique which allows various different VMs employed on top of running kernel. Unalike the existing virtualization approach, a containerization does not execute a VM as a complete OS instance but runs as partial instances of the OS which reduces the CPU and memory overload and also provides the portability due to small size of containers. Docker is a tool to make Linux Containers (LXC) easier to use. Docker containers could be specifically deployed for the applications and systems deployment using lightweight containerization technique which results reducing economical overload instead of VMs over Cloud.

Scalable Cloud Deployment on Commodity Hardware Using OpenStack

OpenStack is a cloud computing project aimed at providing infrastructure as a service (IaaS). In this paper we describe our experience in deploying OpenStack cloud over commodity hardware. We have made an effort to build a large computational facility by sharing the computational resources of our institute through the use of the OpenStack cloud platform. In this paper, we give an overview ofthe OpenStack cloud platform and various services offered by it. We describe two multi-node cloud architectures that we have implemented. In the first architecture, we have deployed the cloud over few machines connected by a closed network. The second architecture allowed us to use geographically separated nodes. We describe the steps required for installation of the cloud for eachof these architectures and provide automated scripts for the same. These automated scripts are available at the following website:http://vnit.ac.in/images/openstack/openstack_grizzly.rar.

An Efficient Algorithm to Compute Delay Set in SPMD Programs

We present compiler analysis for single program multiple data (SPMD) programs that communicate through shared address space. The choice of memory consistency model is sequential consistency as defined by Lamport [9]. Previous research has shown that these programs require cycle detection to perform any kind of code re-ordering either at hardware or software. So far, the best known cycle detection algorithm for SPMD programs has been given by Krishnamurthy et al [5, 6, 8]. Their algorithm computes a delay set that is composed of those memory access pairs that if re-ordered either by hardware or software may cause violation of sequential consistency. This delay set is computed in O(m 3) time where m is the number of read/write accesses. In this paper, we present O(m 2) algorithm for computing analogous delay set for SPMD programs that are used in practice. These programs must be structured with the property that all the variables are initialized before their value is read.

Plane triangulations are 6-partitionable

Given a graph G = (V,E) and k positive integers n1,n2 ..... nk such that Σki = 1 ni = |V|,we wish to find a partition P1,P2,..... Pk of the vertex set V such that |Pi| = ni and Pi induces a connected subgraph of G for all i, 1 ≤ i ≤ k. Such a partition is called a k-partition of G. A graph G with n vertices is said to be k-partitionable if there exists a k-partition of G for any partition of n into k parts. Lovasz (Acta Math. Acad. Sci. Hungar. 30 (1977) 241) showed that k-connected graphs are k-partitionable. In this paper we prove that plane triangulations are 6-partitionable. This result is the best possible as there exist plane triangulations which are not 7-partitionable.

Review of the systems biology of the immune system using agent-based models

The immune system is an inherent protection system in vertebrate animals including human beings that exhibit properties such as self-organisation, self-adaptation, learning, and recognition. It interacts with the other allied systems such as the gut and lymph nodes. There is a need for immune system modelling to know about its complex internal mechanism, to understand how it maintains the homoeostasis, and how it interacts with the other systems. There are two types of modelling techniques used for the simulation of features of the immune system: equation-based modelling (EBM) and agent-based modelling. Owing to certain shortcomings of the EBM, agent-based modelling techniques are being widely used. This technique provides various predictions for disease causes and treatments; it also helps in hypothesis verification. This study presents a review of agent-based modelling of the immune system and its interactions with the gut and lymph nodes. The authors also review the modelling of immune system interactions during tuberculosis and cancer. In addition, they also outline the future research directions for the immune system simulation through agent-based techniques such as the effects of stress on the immune system, evolution of the immune system, and identification of the parameters for a healthy immune system.

Physical to Virtual Migration of Ubuntu System on OpenStack Cloud

Cloud computing is an evolving technology which provides reliable computing resources as a utility rather than having to build and maintain computing infrastructures in-house. Today users and organizations wants to migrate from physical system to a virtual cloud instance. In other words, users want to migrate a traditional operating system, pre-installed on their physical system into a virtual machine instance running on Cloud. Most of the time user requires instance configuration to be exactly same as that of his/her personal physical system. In this paper, we have implemented a process of migration of physical system to virtual OpenStack cloud instance. We have achieved this with the use of system images of the physical system and created a semi-automated script. The script is available at following website: https://sites.google.com/site/physicaltovirtualmigrationofos/

A deterministic model of the adult subventricular neurogenesis

There is a significant interest in studying adult subventricular neurogenesis to understand its biological function. Adult subventricular neurogenesis results in migration of neuronal precursors from subventricular zone to the olfactory bulb through the rostral migratory stream where they get converted to neurons. In this paper, we present a deterministic model of this phenomenon. It demonstrates the steady production of sufficient number of neurons. We prove that our model is biologically feasible and it overcomes the limitations of previously reported models. We believe that our model will help in devising experiments to further improve the understanding of adult subventricular neurogenesis. We have performed agent-based simulation of the model proposed in this paper. The results of this simulation and the program for agent-based simulation is made available on a publicly accessible website.

Agent-Based Deterministic Modeling of the Bone Marrow Homeostasis

Modeling of stem cells not only describes but also predicts how a stem cells environment can control its fate. The first stem cell populations discovered were hematopoietic stem cells (HSCs). In this paper, we present a deterministic model of bone marrow (that hosts HSCs) that is consistent with several of the qualitative biological observations. This model incorporates stem cell death (apoptosis) after a certain number of cell divisions and also demonstrates that a single HSC can potentially populate the entire bone marrow. It also demonstrates that there is a production of sufficient number of differentiated cells (RBCs, WBCs, etc.). We prove that our model of bone marrow is biologically consistent and it overcomes the biological feasibility limitations of previously reported models. The major contribution of our model is the flexibility it allows in choosing model parameters which permits several different simulations to be carried out in silico without affecting the homeostatic properties of the model. We have also performed agent-based simulation of the model of bone marrow system proposed in this paper. We have also included parameter details and the results obtained from the simulation. The program of the agent-based simulation of the proposed model is made available on a publicly accessible website.