Bud Mishra

Model building and model checking for biochemical processes

A central claim of computational systems biology is that, by drawing on mathematical approaches developed in the context of dynamic systems, kinetic analysis, computational theory and logic, it is possible to create powerful simulation, analysis, and reasoning tools for working biologists to decipher existing data, devise new experiments, and ultimately to understand functional properties of genomes, proteomes, cells, organs, and organisms. In this article, a novel computational tool is described that achieves many of the goals of this new discipline. The novelty of this system involves an automaton-based semantics of the temporal evolution of complex biochemical reactions starting from the representation given as a set of differential equations. The related tools also provide ability to qualitatively reason about the systems using a propositional temporal logic that can express an ordered sequence of events succinctly and unambiguously. The implementation of mathematical and computational models in the Simpathica and XSSYS systems is described briefly. Several example applications of these systems to cellular and biochemical processes are presented: the two most prominent are Leibler et al.s repressilator (an artificial synthesized oscillatory network), and Curto-Voit-Sorribas-Cascantes purine metabolism reaction model.

Fine manipulation with multifinger hands

The existence of two- and three-finger grasps in the presence of arbitrarily small friction is shown for 2D and 3D smooth objects using a simple technique. No convexity of the objects is assumed. The existence of finger gaits for rotating a planar object using three and four fingers is proved. Additional results for smooth convex objects which describe two different finger gaits using four fingers are presented. The purpose is to move one or more fingers at any one time and at the same time to maintain a grip with the others, and thereby to move the object further than or in other ways than it could be moved with a fixed grip.<<ETX>>

Optical mapping and its potential for large-scale sequencing projects

Physical mapping has been rediscovered as an important component of large-scale sequencing projects. Restriction maps provide landmark sequences at defined intervals, and high-resolution restriction maps can be assembled from ensembles of single molecules by optical means. Such optical maps can be constructed from both large-insert clones and genomic DNA, and are used as a scaffold for accurately aligning sequence contigs generated by shotgun sequencing.

Turning CARTwheels: an alternating algorithm for mining redescriptions

We present an unusual algorithm involving classification trees---CARTwheels---where two trees are grown in opposite directions so that they are joined at their leaves. This approach finds application in a new data mining task we formulate, called redescription mining. A redescription is a shift-of-vocabulary, or a different way of communicating information about a given subset of data; the goal of redescription mining is to find subsets of data that afford multiple descriptions. We highlight the importance of this problem in domains such as bioinformatics, which exhibit an underlying richness and diversity of data descriptors (e.g., genes can be studied in a variety of ways). CARTwheels exploits the duality between class partitions and path partitions in an induced classification tree to model and mine redescriptions. It helps integrate multiple forms of characterizing datasets, situates the knowledge gained from one dataset in the context of others, and harnesses high-level abstractions for uncovering cryptic and subtle features of data. Algorithm design decisions, implementation details, and experimental results are presented.

A shotgun optical map of the entire Plasmodium falciparum genome

The unicellular parasite Plasmodium falciparum is the cause of human malaria, resulting in 1.7–2.5 million deaths each year. To develop new means to treat or prevent malaria, the Malaria Genome Consortium was formed to sequence and annotate the entire 24.6-Mb genome. The plan, already underway, is to sequence libraries created from chromosomal DNA separated by pulsed-field gel electrophoresis (PFGE). The AT-rich genome of P. falciparum presents problems in terms of reliable library construction and the relative paucity of dense physical markers or extensive genetic resources. To deal with these problems, we reasoned that a high-resolution, ordered restriction map covering the entire genome could serve as a scaffold for the alignment and verification of sequence contigs developed by members of the consortium. Thus optical mapping was advanced to use simply extracted, unfractionated genomic DNA as its principal substrate. Ordered restriction maps (BamHI and NheI) derived from single molecules were assembled into 14 deep contigs corresponding to the molecular karyotype determined by PFGE (ref. 3).

Some discussion of static gripping and its stability

An overview is presented of research done in the area of dextrous manipulation. The main issue has been how to control mechanical hands so that they can perform manipulation task with the same dexterity and sensitivity as the human hands. To achieve sophisticated algorithms for grasping, compliance control, and manipulation, the nature of the contact wrenches, twists, and compliance of the fingers have to be well understood. Here emphasis is on the area of dextrous manipulation encompassed by static grasping. The two main approaches to the problems of grasping reviewed are those motivated by a study of human hands and those motivated by the physical and mechanical properties of grasps such as contact types, number of fingers required to achieve grasp, equilibrium, stability and compliance. >

On the competitiveness of on-line real-time task scheduling

The authors study the performance of online algorithms in environments where no value is obtained for the partial execution of a request. They prove that no online scheduling algorithm can have a competitive factor greater than 0.25 times the optimal. They further refine this bound by considering the effect of the loading factor. Other models of task systems (for example, tasks systems consisting of many types of task requests), are considered. Similar upper bounds on the competitive factor that can be made by online scheduling algorithms in these environments are proved. It is shown that the performance bound of 0.25 is tight by means of a simple online uniprocessor scheduling algorithm has a competitive factor of 1/4. The authors extend the discussion to systems with dual processors. They show that the upper bound for the dual-processor online scheduling problem is 1/2 if all tasks have the same value density. This bound is tight if the tasks all also have zero laxity.<<ETX>>

Algorithmic algebraic model checking i: challenges from systems biology

In this paper, we suggest a possible confluence of the theory of hybrid automata and the techniques of algorithmic algebra to create a computational basis for systems biology. We describe a method to compute bounded reachability by combining Taylor polynomials and cylindric algebraic decomposition algorithms. We discuss the power and limitations of the framework we propose and we suggest several possible extensions. We briefly show an application to the study of the Delta-Notch protein signaling system in biology.

Reevaluating assembly evaluations with feature response curves: GAGE and assemblathons.

In just the last decade, a multitude of bio-technologies and software pipelines have emerged to revolutionize genomics. To further their central goal, they aim to accelerate and improve the quality of de novo whole-genome assembly starting from short DNA sequences/reads. However, the performance of each of these tools is contingent on the length and quality of the sequencing data, the structure and complexity of the genome sequence, and the resolution and quality of long-range information. Furthermore, in the absence of any metric that captures the most fundamental “features” of a high-quality assembly, there is no obvious recipe for users to select the most desirable assembler/assembly. This situation has prompted the scientific community to rely on crowd-sourcing through international competitions, such as Assemblathons or GAGE, with the intention of identifying the best assembler(s) and their features. Somewhat circuitously, the only available approach to gauge de novo assemblies and assemblers relies solely on the availability of a high-quality fully assembled reference genome sequence. Still worse, reference-guided evaluations are often both difficult to analyze, leading to conclusions that are difficult to interpret. In this paper, we circumvent many of these issues by relying upon a tool, dubbed , which is capable of evaluating de novo assemblies from the read-layouts even when no reference exists. We extend the FRCurve approach to cases where lay-out information may have been obscured, as is true in many deBruijn-graph-based algorithms. As a by-product, FRCurve now expands its applicability to a much wider class of assemblers – thus, identifying higher-quality members of this group, their inter-relations as well as sensitivity to carefully selected features, with or without the support of a reference sequence or layout for the reads. The paper concludes by reevaluating several recently conducted assembly competitions and the datasets that have resulted from them.

Copy Number Variant Analysis of Human Embryonic Stem Cells

Differences between individual DNA sequences provide the basis for human genetic variability. Forms of genetic variation include single‐nucleotide polymorphisms, insertions/duplications, deletions, and inversions/translocations. The genome of human embryonic stem cells (hESCs) has been characterized mainly by karyotyping and comparative genomic hybridization (CGH), techniques whose relatively low resolution at 2–10 megabases (Mb) cannot accurately determine most copy number variability, which is estimated to involve 10%–20% of the genome. In this brief technical study, we examined HSF1 and HSF6 hESCs using array‐comparative genomic hybridization (aCGH) to determine copy number variants (CNVs) as a higher‐resolution method for characterizing hESCs. Our approach used five samples for each hESC line and showed four consistent CNVs for HSF1 and five consistent CNVs for HSF6. These consistent CNVs included amplifications and deletions that ranged in size from 20 kilobases to 1.48 megabases, involved seven different chromosomes, were both shared and unique between hESCs, and were maintained during neuronal stem/progenitor cell differentiation or drug selection. Thirty HSF1 and 40 HSF6 less consistently scored but still highly significant candidate CNVs were also identified. Overall, aCGH provides a promising approach for uniquely identifying hESCs and their derivatives and highlights a potential genomic source for distinct differentiation and functional potentials that lower‐resolution karyotype and CGH techniques could miss.