Computational Biology and Language

Current scientific research is characterized by increasing specialization, accumulating knowledge at a high speed due to parallel advances in a multitude of sub-disciplines. Recent estimates suggest that human knowledge doubles every two to three years – and with the advances in information and communication technologies, this wide body of scientific knowledge is available to anyone, anywhere, anytime. This may also be referred to as ambient intelligence – an environment characterized by plentiful and available knowledge. The bottleneck in utilizing this knowledge for specific applications is not accessing but assimilating the information and transforming it to suit the needs for a specific application. The increasingly specialized areas of scientific research often have the common goal of converting data into insight allowing the identification of solutions to scientific problems. Due to this common goal, there are strong parallels between different areas of applications that can be exploited and used to cross-fertilize different disciplines. For example, the same fundamental statistical methods are used extensively in speech and language processing, in materials science applications, in visual processing and in biomedicine. Each sub-discipline has found its own specialized methodologies making these statistical methods successful to the given application. The unification of specialized areas is possible because many different problems can share strong analogies, making the theories developed for one problem applicable to other areas of research. It is the goal of this paper to demonstrate the utility of merging two disparate areas of applications to advance scientific research. The merging process requires cross-disciplinary collaboration to allow maximal exploitation of advances in one sub-discipline for that of another. We will demonstrate this general concept with the specific example of merging language technologies and computational biology.

The 3 Technologies

The technology scene in India is at one and the same time promising, frustrating and fascinating. Three broad areas in technology development can be distinguished. The first is relatively small scale; it is typified by the absorption of products of the industrial revolution into the repertoire of the Indian artisan and craftsman, examples being diesel engines from Kolhapur and centrifugal pumps from Coimbatore. The second class is essentially 'state technology', developed at public expense by national commissions: agriculture, atomic energy and space are examples. There is a vast third area in both private and public sector, covering products for the urban consumer and the state (e.g. r defence); this area has largely remained colonial. The factors affecting the three areas of technology are described and analysed from the point of view of an Indian scientistengineer; and it is concluded that the enormous potential of the country's human and mat.erial resources is not only unrealized, but even unrecognized as yet.

Renewable energy and energy conservation technologies

Energy systems should be consistent with environmental, economic and social sustainability in order to ensure regional sustainable development. This enhances both current and future potential to meet the human needs and aspirations. Sustainable development, a process of change, in which, the exploitation of resources, the direction of investments , the orientation of technological development and institutional change are in harmony. National energy programme should prioritize the development of renewable energy sources, which offer the potentially huge sources of primary energy. The path for sustainability in the next millennium is the low energy path through wise use of energy. Energy conservation and energy efficiency measures would certainly result in meeting the energy demand with as little as half the primary supply at current levels. This requires profound structural changes in socio-economic and institutional arrangements. Environmentally sound, technically and economically viable energy pathways will sustain human progress in the long term future giving a fair and equitable share of the underprivileged and poor of the developing countries. Renewable energy is considered by some as the only hope for the survival of planet yet by others it is viewed as a marginal resource with limited resource. All too often, however, the facts behind the role that renewable energy can, and will, play in the regional energy scene are disguised or ignored as rival camps distort the evidence to suit their own objectives. It was in the light of this confusion that the Energy Research Group at Centre for Ecological Sciences, Indian Institute of Science undertook investigation in Kolar and Uttara Kannada Districts in Karnataka State, India to identify the potential contribution of several types of renewable energy sources: Solar, Wind, Hydro, Bioenergy, etc.

Extracting Three Dimensional Surface Model of Human Kidney from the Visible Human Data Set using Free Software

Three dimensional digital model of a representative human kidney is needed for a surgical simulator that is capable of simulating a laparoscopic surgery involving kidney. Buying a three dimensional computer model of a representative human kidney, or reconstructing a human kidney from an image sequence using commercial software, both involve (sometimes significant amount of) money. In this paper, author has shown that one can obtain a three dimensional surface model of human kidney by making use of images from the Visible Human Data Set and a few free software packages (ImageJ, ITK-SNAP, and MeshLab in particular). Images from the Visible Human Data Set, and the software packages used here, both do not cost anything. Hence, the practice of extracting the geometry of a representative human kidney for free, as illustrated in the present work, could be a free alternative to the use of expensive commercial software or to the purchase of a digital model.

Suite of tools for statistical N-gram language modeling for pattern mining in whole genome sequences

Genome sequences contain a number of patterns that have biomedical significance. Repetitive sequences of various kinds are a primary component of most of the genomic sequence patterns. We extended the suffix-array based Biological Language Modeling Toolkit to compute n-gram frequencies as well as n-gram language-model based perplexity in windows over the whole genome sequence to find biologically relevant patterns. We present the suite of tools and their application for analysis on whole human genome sequence.

Variation at Diabetes- and Obesity-Associated Loci May Mirror Neutral Patterns of Human Population Diversity and Diabetes Prevalence in India

South Asian populations harbor a high degree of genetic diversity, due in part to demographic history. Two studies on genome-wide variation in Indian populations have shown that most Indian populations show varying degrees of admixture between ancestral north Indian and ancestral south Indian components. As a result of this structure, genetic variation in India appears to follow a geographic cline. Similarly, Indian populations seem to show detectable differences in diabetes and obesity prevalence between different geographic regions of the country. We tested the hypothesis that genetic variation at diabetes-and obesity-associated loci may be potentially related to different genetic ancestries. We genotyped 2977 individuals from 61 populations across India for 18 SNPs in genes implicated in T2D and obesity. We examined patterns of variation in allele frequency across different geographical gradients and considered state of origin and language affiliation. Our results show that most of the 18 SNPs show no significant correlation with latitude, the geographic cline reported in previous studies, or by language family. Exceptions include KCNQ1 with latitude and THADA and JAK1 with language, which suggests that genetic variation at previously ascertained diabetes-associated loci may only partly mirror geographic patterns of genome-wide diversity in Indian populations.

Efficient Dictionary for Salted Password Analysis

User authentication is essential for accessing computing resources, network resources, email accounts, online portals etc. To authenticate a user, system stores user credentials (user id and password pair) in system. It has been an interested field problem to discover user password from a system and similarly protecting them against any such possible attack. In this work we show that passwords are still vulnerable to hash chain based and efficient dictionary attacks. Human generated passwords use some identifiable patterns. We have analysed a sample of 19 million passwords, of different lengths, available online and studied the distribution of the symbols in the password strings. We show that the distribution of symbols in user passwords is affected by the native language of the user. From symbol distributions we can build smart and efficient dictionaries, which are smaller in size and their coverage of plausible passwords from Key-space is large. These smart dictionaries make dictionary based attacks practical.