84 research outputs found
Evidence for low homology between mammalian leptin and chicken leptin-like gene sequences
Leptin is a 167-amino acid hormone produced chiefly by adipocytes. It plays an important role in regulation of food intake, energy metabolism and reproduction in mammals. However, a leptin gene homologue has yet to be cloned in a non-mammalian vertebrate. The aim of this thesis was to establish the existence of a leptin gene homologue in the domestic chicken (Gallus gallus) genome, and to determine the degree of sequence identity with mammalian leptin genes, and with a putative chicken leptin sequence published during the course of the thesis work. An initial attempt was made to
clone the chicken leptin gene by heterologous RT-PCR using degenerate primers to conserved regions of mammalian leptin sequences. However, no leptin-like products were amplified from chicken adipose tissue and liver cDNAs,or from genomic DNA. RTPCR was also used to test the existence of a published chicken leptin cDNA sequence that shares 95% identity with mouse leptin at the nucleotide level. When PCR primers identical to the mouse and published chicken leptin sequences were used, no PCR product sharing close similarity to the mouse leptin sequence were generated from any chicken templates, whereas amplification of mouse leptin leptin sequences was consistently obtained from control mouse templates. Following the failure to clone the
chicken leptin by RT-PCR, evidence for the existence of a mammalian-like leptin in the chicken genome was sought by Southern analysis. Southern blots under low stringency
hybridization and washing conditions revealed hybridization of a mouse leptin probe to chicken genomic DNA. With high stringency washing, the chicken signal disappeared,
while those from sheep and mouse genomic DNA remained. Screening of a chicken adipose tissue cDNA library, and chicken genomic DNA and cosmid libraries with the
same mouse probe failed to isolate a chicken leptin homologue. Collectively, these results indicate that if a chicken leptin homologue exists in the chicken genome, it is likely to be of low homology to mammalian leptin sequences. The results do not support the existence of a mouse-like leptin sequence in the chicken genome, an assertion supported
by theoretical analysis of the molecular evolution of leptin based on the rate of synonymous substitution. This analysis indicated that the probability that the chicken and mouse leptin sequences are 95% identical, is less than one in a million
Derandomized Graph Product Results using the Low Degree Long Code
In this paper, we address the question of whether the recent derandomization
results obtained by the use of the low-degree long code can be extended to
other product settings. We consider two settings: (1) the graph product results
of Alon, Dinur, Friedgut and Sudakov [GAFA, 2004] and (2) the "majority is
stablest" type of result obtained by Dinur, Mossel and Regev [SICOMP, 2009] and
Dinur and Shinkar [In Proc. APPROX, 2010] while studying the hardness of
approximate graph coloring.
In our first result, we show that there exists a considerably smaller
subgraph of which exhibits the following property (shown for
by Alon et al.): independent sets close in size to the
maximum independent set are well approximated by dictators.
The "majority is stablest" type of result of Dinur et al. and Dinur and
Shinkar shows that if there exist two sets of vertices and in
with very few edges with one endpoint in and another in
, then it must be the case that the two sets and share a single
influential coordinate. In our second result, we show that a similar "majority
is stablest" statement holds good for a considerably smaller subgraph of
. Furthermore using this result, we give a more efficient
reduction from Unique Games to the graph coloring problem, leading to improved
hardness of approximation results for coloring
Streaming algorithms for language recognition problems
We study the complexity of the following problems in the streaming model.
Membership testing for \DLIN We show that every language in \DLIN\ can be
recognised by a randomized one-pass space algorithm with inverse
polynomial one-sided error, and by a deterministic p-pass space
algorithm. We show that these algorithms are optimal.
Membership testing for \LL For languages generated by \LL grammars
with a bound of on the number of nonterminals at any stage in the left-most
derivation, we show that membership can be tested by a randomized one-pass
space algorithm with inverse polynomial (in ) one-sided error.
Membership testing for \DCFL We show that randomized algorithms as efficient
as the ones described above for \DLIN\ and \LL(k) (which are subclasses of
\DCFL) cannot exist for all of \DCFL: there is a language in \VPL\ (a subclass
of \DCFL) for which any randomized p-pass algorithm with error bounded by
must use space.
Degree sequence problem We study the problem of determining, given a sequence
and a graph , whether the degree sequence of is
precisely . We give a randomized one-pass space
algorithm with inverse polynomial one-sided error probability. We show that our
algorithms are optimal.
Our randomized algorithms are based on the recent work of Magniez et al.
\cite{MMN09}; our lower bounds are obtained by considering related
communication complexity problems
On Fortification of Projection Games
A recent result of Moshkovitz \cite{Moshkovitz14} presented an ingenious
method to provide a completely elementary proof of the Parallel Repetition
Theorem for certain projection games via a construction called fortification.
However, the construction used in \cite{Moshkovitz14} to fortify arbitrary
label cover instances using an arbitrary extractor is insufficient to prove
parallel repetition. In this paper, we provide a fix by using a stronger graph
that we call fortifiers. Fortifiers are graphs that have both and
guarantees on induced distributions from large subsets. We then show
that an expander with sufficient spectral gap, or a bi-regular extractor with
stronger parameters (the latter is also the construction used in an independent
update \cite{Moshkovitz15} of \cite{Moshkovitz14} with an alternate argument),
is a good fortifier. We also show that using a fortifier (in particular
guarantees) is necessary for obtaining the robustness required for
fortification.Comment: 19 page
Semi-Supervised Recurrent Neural Network for Adverse Drug Reaction Mention Extraction
Social media is an useful platform to share health-related information due to
its vast reach. This makes it a good candidate for public-health monitoring
tasks, specifically for pharmacovigilance. We study the problem of extraction
of Adverse-Drug-Reaction (ADR) mentions from social media, particularly from
twitter. Medical information extraction from social media is challenging,
mainly due to short and highly information nature of text, as compared to more
technical and formal medical reports.
Current methods in ADR mention extraction relies on supervised learning
methods, which suffers from labeled data scarcity problem. The State-of-the-art
method uses deep neural networks, specifically a class of Recurrent Neural
Network (RNN) which are Long-Short-Term-Memory networks (LSTMs)
\cite{hochreiter1997long}. Deep neural networks, due to their large number of
free parameters relies heavily on large annotated corpora for learning the end
task. But in real-world, it is hard to get large labeled data, mainly due to
heavy cost associated with manual annotation. Towards this end, we propose a
novel semi-supervised learning based RNN model, which can leverage unlabeled
data also present in abundance on social media. Through experiments we
demonstrate the effectiveness of our method, achieving state-of-the-art
performance in ADR mention extraction.Comment: Accepted at DTMBIO workshop, CIKM 2017. To appear in BMC
Bioinformatics. Pls cite that versio
Super-polylogarithmic hypergraph coloring hardness via low-degree long codes
We prove improved inapproximability results for hypergraph coloring using the
low-degree polynomial code (aka, the 'short code' of Barak et. al. [FOCS 2012])
and the techniques proposed by Dinur and Guruswami [FOCS 2013] to incorporate
this code for inapproximability results. In particular, we prove
quasi-NP-hardness of the following problems on -vertex hyper-graphs:
* Coloring a 2-colorable 8-uniform hypergraph with
colors.
* Coloring a 4-colorable 4-uniform hypergraph with
colors.
* Coloring a 3-colorable 3-uniform hypergraph with colors.
In each of these cases, the hardness results obtained are (at least)
exponentially stronger than what was previously known for the respective cases.
In fact, prior to this result, polylog n colors was the strongest quantitative
bound on the number of colors ruled out by inapproximability results for
O(1)-colorable hypergraphs.
The fundamental bottleneck in obtaining coloring inapproximability results
using the low- degree long code was a multipartite structural restriction in
the PCP construction of Dinur-Guruswami. We are able to get around this
restriction by simulating the multipartite structure implicitly by querying
just one partition (albeit requiring 8 queries), which yields our result for
2-colorable 8-uniform hypergraphs. The result for 4-colorable 4-uniform
hypergraphs is obtained via a 'query doubling' method. For 3-colorable
3-uniform hypergraphs, we exploit the ternary domain to design a test with an
additive (as opposed to multiplicative) noise function, and analyze its
efficacy in killing high weight Fourier coefficients via the pseudorandom
properties of an associated quadratic form.Comment: 25 page
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